CN118331072A - Air flow rate self-adaptive control modeling method for air water generator - Google Patents
Air flow rate self-adaptive control modeling method for air water generator Download PDFInfo
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Abstract
The invention relates to the technical field of flow rate control, in particular to an air flow rate self-adaptive control modeling method of an air water generator. The method comprises the following steps: the air flow rate sensor and the environmental parameter sensor are arranged and environmental parameters are acquired and processed to obtain air flow rate data of the air water generator, environmental temperature data of the air water generator and environmental humidity data of the air water generator; acquiring real-time water production data of the air water generator, and performing water production efficiency evaluation analysis and efficiency environmental impact optimization to obtain the actual water production efficiency of the air water generator; performing parameter vector conversion and flow velocity relation modeling analysis on air flow velocity data of the air water making machine and actual water making efficiency of the air water making machine to generate an air flow velocity water making efficiency relation model; and carrying out working parameter adjustment analysis and self-adaptive regulation and control treatment on the air water generator to obtain an air flow velocity regulation and control result of the air water generator. The invention can adjust the parameters of the water generator in real time to control the change of the air flow rate.
Description
Technical Field
The invention relates to the technical field of flow rate control, in particular to an air flow rate self-adaptive control modeling method of an air water generator.
Background
Currently, along with the increasing shortage of global water resources, people become particularly critical to the utilization and management of water resources, traditional water resource acquisition modes often depend on natural water sources such as groundwater, rivers or lakes, and meanwhile, along with the influence of factors such as population growth and climate change, the supply of the traditional water resources faces various challenges, such as groundwater level drop and water pollution, so that the problems are increasingly prominent. Therefore, finding a new water resource acquisition path is urgent. The air water generator is used as a novel water resource acquisition technology, and can provide an innovative solution for solving the problem of water resource shortage by extracting water from the air. In such a background, air water production technology has been developed, which uses water vapor in air to condense and extract by a specific process, thereby enabling effective utilization and regeneration of water resources. However, the conventional control method of the air water generator is often based on an empirical formula or a simple control algorithm, and cannot sufficiently adapt to the air flow rate change under different environments, so that the water production efficiency is unstable.
Disclosure of Invention
Based on the foregoing, the present invention is needed to provide a modeling method for adaptive control of air flow rate of an air water generator, so as to solve at least one of the above-mentioned technical problems.
In order to achieve the purpose, the air flow rate self-adaptive control modeling method of the air water generator comprises the following steps:
Step S1: the air flow rate sensor and the environmental parameter sensor are distributed around the air water generator, and the air flow rate sensor and the environmental parameter sensor are used for collecting and processing environmental parameters of the air water generator so as to obtain air flow rate data of the air water generator, environmental temperature data of the air water generator and environmental humidity data of the air water generator;
step S2: acquiring real-time water production data of the air water production machine, and performing water production efficiency evaluation analysis on the air water production machine based on the real-time water production data of the air water production machine so as to obtain the real-time water production efficiency of the air water production machine; according to the environmental temperature data of the air water generator and the environmental humidity data of the air water generator, optimizing the efficiency and environmental influence of the air water generator on the real-time water production efficiency of the air water generator, and obtaining the actual water production efficiency of the air water generator;
step S3: performing parameter vector conversion on air flow rate data of the air water making machine and actual water making efficiency of the air water making machine to obtain an air flow rate parameter vector of the air water making machine and a real-time water making efficiency parameter vector of the air water making machine; performing flow velocity relation modeling analysis on the air flow velocity parameter vector of the air water generator based on the real-time water production efficiency parameter vector of the air water generator so as to generate an air flow velocity water production efficiency relation model;
Step S4: based on the air flow rate water production efficiency relation model, the real-time water production efficiency of the air water production machine and the air flow rate data of the air water production machine, carrying out working parameter adjustment analysis on the air water production machine by utilizing an adaptive control algorithm so as to generate an adaptive control strategy for working parameters of the air water production machine; and carrying out self-adaptive regulation and control treatment according to the self-adaptive control strategy of the working parameters of the air water making machine to obtain the air flow rate regulation and control result of the air water making machine.
According to the invention, the air flow rate sensor and the environment parameter sensor are distributed around the air water generator, and the ambient environment of the air water generator is monitored and collected through the sensors in real time, so that key environment data including information such as air flow rate, environment temperature and humidity can be collected, the collection of the data can provide a basis for subsequent analysis and optimization, and the stable operation of the air water generator under different environment conditions is ensured. Secondly, the water production condition of the air water generator is acquired through real-time acquisition, and the key of the step is that the instant monitoring and data acquisition of the current production water quantity of the air water generator can be realized, so that the current working state and water yield condition of the air water generator can be known through acquiring real-time water production data, and a data base is provided for subsequent analysis and optimization. Through carrying out water production efficiency evaluation analysis to the air water machine based on the real-time water production data of the air water machine, the step can realize the evaluation analysis to the water production efficiency of the air water machine, so that the production efficiency and the resource utilization condition of the air water machine can be comprehensively known, and an important reference is provided for improving the production efficiency and reducing the cost. Meanwhile, the efficiency and environmental influence optimization is carried out on the real-time water production efficiency of the air water production machine according to the environmental temperature data and the environmental humidity data of the air water production machine, so that the influence of environmental factors on the water production efficiency can be considered, and the actual water production efficiency of the air water production machine can be more accurately estimated through the optimization and adjustment of the environmental data, so that the production performance and the resource utilization efficiency of the air water production machine under different environmental conditions are improved. Then, through carrying out parameter vector conversion to air flow rate data of the air water making machine and actual water making efficiency of the air water making machine, the key of the step is that the original data can be converted into a form which can be used for subsequent analysis, and through the conversion of the parameter vector, the relation between the air flow rate and the water making efficiency can be better understood and described, and a foundation is laid for subsequent modeling and analysis. The linear regression analysis algorithm is used for carrying out flow velocity relation modeling analysis on the air flow velocity parameter vector of the air water generator based on the real-time water production efficiency parameter vector of the air water generator, and a linear relation model between the air flow velocity and the water production efficiency can be established through the model construction process, so that the air flow velocity under the corresponding water production efficiency is predicted, the establishment of the model has important significance for understanding the influence of the water production efficiency on the air flow velocity, a foundation is provided for subsequent model verification and optimization, and the air flow velocity change under different environments can be better adapted, so that a reliable basis is provided for air flow velocity control and optimization of the air water generator. Finally, by combining an air flow rate water production efficiency relation model, an air water production machine real-time water production efficiency and air flow rate data analysis of the air water production machine, deviation and uncertainty between model prediction and actual air flow rate are identified, and by utilizing a self-adaptive control algorithm to carry out working parameter adjustment analysis on the air water production machine, the working parameters of the air water production machine can be dynamically adjusted according to actual conditions so as to realize optimization and stabilization of water production efficiency, thus the self-adaptive control algorithm can adjust parameters in real time according to feedback signals and error items, the air water production machine can adapt to continuously changing working environment and conditions, and the stability and robustness of the air water production machine are improved, The adjustment strategy can effectively cope with uncertainty and variability, and ensures that the air water generator is always in an optimal working state. In addition, the corresponding air flow speed deviation condition is adaptively regulated and controlled according to the air water making machine working parameter adaptive control strategy, so that the air flow speed can be regulated and controlled in real time, the air water making machine can be kept in a preset working state by adaptively regulating and controlling the change of the flow speed error in time, the water making efficiency and the stability of the air water making machine can be improved through the regulating and controlling result, and the air water making machine can be ensured to operate efficiently under different working conditions.
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Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of a non-limiting implementation, made with reference to the accompanying drawings in which:
FIG. 1 is a schematic flow chart of the steps of the modeling method for adaptive control of air flow rate of an air water generator;
FIG. 2 is a detailed step flow chart of step S2 in FIG. 1;
Fig. 3 is a detailed step flow chart of step S23 in fig. 2.
Detailed Description
The following is a clear and complete description of the technical method of the present patent in conjunction with the accompanying drawings, and it is evident that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.
Furthermore, the drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. The functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor methods and/or microcontroller methods.
It will be understood that, although the terms "first," "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
In order to achieve the above objective, referring to fig. 1 to 3, the present invention provides a modeling method for adaptive control of air flow rate of an air water generator, the method comprising the following steps:
Step S1: the air flow rate sensor and the environmental parameter sensor are distributed around the air water generator, and the air flow rate sensor and the environmental parameter sensor are used for collecting and processing environmental parameters of the air water generator so as to obtain air flow rate data of the air water generator, environmental temperature data of the air water generator and environmental humidity data of the air water generator;
step S2: acquiring real-time water production data of the air water production machine, and performing water production efficiency evaluation analysis on the air water production machine based on the real-time water production data of the air water production machine so as to obtain the real-time water production efficiency of the air water production machine; according to the environmental temperature data of the air water generator and the environmental humidity data of the air water generator, optimizing the efficiency and environmental influence of the air water generator on the real-time water production efficiency of the air water generator, and obtaining the actual water production efficiency of the air water generator;
step S3: performing parameter vector conversion on air flow rate data of the air water making machine and actual water making efficiency of the air water making machine to obtain an air flow rate parameter vector of the air water making machine and a real-time water making efficiency parameter vector of the air water making machine; performing flow velocity relation modeling analysis on the air flow velocity parameter vector of the air water generator based on the real-time water production efficiency parameter vector of the air water generator so as to generate an air flow velocity water production efficiency relation model;
Step S4: based on the air flow rate water production efficiency relation model, the real-time water production efficiency of the air water production machine and the air flow rate data of the air water production machine, carrying out working parameter adjustment analysis on the air water production machine by utilizing an adaptive control algorithm so as to generate an adaptive control strategy for working parameters of the air water production machine; and carrying out self-adaptive regulation and control treatment according to the self-adaptive control strategy of the working parameters of the air water making machine to obtain the air flow rate regulation and control result of the air water making machine.
In the embodiment of the present invention, please refer to fig. 1, which is a schematic diagram of an air flow rate adaptive control modeling method of an air water generator, in this example, the air flow rate adaptive control modeling method of the air water generator includes the following steps:
Step S1: the air flow rate sensor and the environmental parameter sensor are distributed around the air water generator, and the air flow rate sensor and the environmental parameter sensor are used for collecting and processing environmental parameters of the air water generator so as to obtain air flow rate data of the air water generator, environmental temperature data of the air water generator and environmental humidity data of the air water generator;
According to the embodiment of the invention, the corresponding air flow rate sensor and the corresponding environmental parameter sensor (comprising the temperature sensor and the humidity sensor) are arranged in the surrounding area of the air water generator, and the environmental parameters of the air water generator are monitored and collected in real time by using the arranged air flow rate sensor and the environmental parameter sensor so as to collect key environmental data including information such as air flow rate, environmental temperature and humidity, and the like, and meanwhile, the collected data are subjected to data preprocessing, so that the air flow rate data of the air water generator, the environmental temperature data of the air water generator and the environmental humidity data of the air water generator are finally obtained.
Step S2: acquiring real-time water production data of the air water production machine, and performing water production efficiency evaluation analysis on the air water production machine based on the real-time water production data of the air water production machine so as to obtain the real-time water production efficiency of the air water production machine; according to the environmental temperature data of the air water generator and the environmental humidity data of the air water generator, optimizing the efficiency and environmental influence of the air water generator on the real-time water production efficiency of the air water generator, and obtaining the actual water production efficiency of the air water generator;
According to the embodiment of the invention, the water production condition of the air water generator is acquired in real time by using the sensor equipment, so that the current production water quantity of the air water generator is monitored in real time and data acquisition is realized, and real-time water production data of the air water generator are obtained. Meanwhile, time sequence analysis is carried out on real-time water production data of the air water production machine acquired in real time by using methods such as trend analysis, periodical analysis and the like so as to know the change trend of the water production quantity of the air water production machine along with time, and statistical analysis is carried out on the water production efficiency of the corresponding air water production machine by analyzing the water production machine water production rate and the influence factors between the water production efficiency and the water production performance so as to calculate the real-time water production efficiency under different conditions, and the comprehensive influence efficiency of the factors such as the water production quantity, the energy efficiency ratio and the like on the water production performance can be reflected, so that the real-time water production efficiency of the air water production machine is obtained. Then, the real-time water production efficiency of the air water production machine is analyzed by using an influence evaluation algorithm according to the environmental temperature data of the air water production machine and the change condition of the environmental humidity data of the air water production machine, so as to explore the influence relation between the environmental temperature and humidity change and the real-time water production efficiency to determine the influence degree of the environmental temperature and humidity change on the water production efficiency, and the real-time water production efficiency of the corresponding air water production machine is improved and optimized according to the influence degree obtained by analysis, so that the operation strategy or the environmental control mode of the air water production machine is adjusted by implementing corresponding improvement measures (including adjusting the working parameters of the water production machine, optimizing the water production process and the like), the expected water production efficiency is improved, the air water production machine can maintain the high-efficiency and stable water production performance under various environmental conditions, and finally the actual water production efficiency of the air water production machine is obtained.
Step S3: performing parameter vector conversion on air flow rate data of the air water making machine and actual water making efficiency of the air water making machine to obtain an air flow rate parameter vector of the air water making machine and a real-time water making efficiency parameter vector of the air water making machine; performing flow velocity relation modeling analysis on the air flow velocity parameter vector of the air water generator based on the real-time water production efficiency parameter vector of the air water generator so as to generate an air flow velocity water production efficiency relation model;
according to the embodiment of the invention, the air flow rate data of the air water making machine and the actual water making efficiency of the air water making machine are subjected to parameter division and converted into vector forms according to a certain time interval, the collected air flow rate data and water making efficiency data are arranged into vector forms according to a certain rule and standard, the air flow rate parameter vector is subjected to model training by using a linear regression analysis algorithm aiming at the water making efficiency parameter vector so as to be used for researching the linear relation between the water making efficiency and the air flow rate, the real-time water making efficiency parameter vector is used as an independent variable, the air flow rate parameter vector is used as a dependent variable to train a model, meanwhile, the trained air flow rate linear relation model is subjected to model verification by using a corresponding test set and combining a cross verification technology so as to verify the generalization capability of the model on new data and evaluate the accuracy and reliability of the model, and the model is optimized according to a verification result so as to adjust the super-parameter of the model to improve the linear relation between the predicted air flow rate and the water making efficiency, and finally the air flow rate water making efficiency relation model is generated.
Step S4: based on the air flow rate water production efficiency relation model, the real-time water production efficiency of the air water production machine and the air flow rate data of the air water production machine, carrying out working parameter adjustment analysis on the air water production machine by utilizing an adaptive control algorithm so as to generate an adaptive control strategy for working parameters of the air water production machine; and carrying out self-adaptive regulation and control treatment according to the self-adaptive control strategy of the working parameters of the air water making machine to obtain the air flow rate regulation and control result of the air water making machine.
The embodiment of the invention carries out model prediction of corresponding air flow rate by inputting the real-time water production efficiency of the air water production machine before non-optimization into a constructed air flow rate water production efficiency relation model so as to infer the air flow rate under the corresponding water production efficiency based on the existing real-time water production efficiency data and a linear relation model, compares and carries out error analysis on air flow rate data and model prediction data obtained by measuring the air water production machine in the actual operation process by using an error statistical analysis method so as to compare the difference between the real-time flow rate and the model prediction, and identifies the deviation and uncertainty between the model prediction and the actual air flow rate, corresponding strategies for adjusting working parameters of the air water machine are dynamically generated according to the change condition of the air flow rate error item, namely, parameter adjustment schemes which should be adopted under different error conditions are determined, so that the air water machine can adapt to continuously changing working environments and conditions, including control strategies such as adjusting the rotating speed of a fan, increasing the area of a moisture absorption film, heating temperature and the like, then, the corresponding air flow rate errors are adaptively regulated and controlled through the generated control strategies, so that the working parameters of the air water machine are dynamically adjusted according to the control strategies, the optimal control of the air flow rate is realized, the air water machine can be ensured to operate efficiently under different working conditions, and finally, the air flow rate regulation result of the air water machine is obtained.
According to the invention, the air flow rate sensor and the environment parameter sensor are distributed around the air water generator, and the ambient environment of the air water generator is monitored and collected through the sensors in real time, so that key environment data including information such as air flow rate, environment temperature and humidity can be collected, the collection of the data can provide a basis for subsequent analysis and optimization, and the stable operation of the air water generator under different environment conditions is ensured. Secondly, the water production condition of the air water generator is acquired through real-time acquisition, and the key of the step is that the instant monitoring and data acquisition of the current production water quantity of the air water generator can be realized, so that the current working state and water yield condition of the air water generator can be known through acquiring real-time water production data, and a data base is provided for subsequent analysis and optimization. Through carrying out water production efficiency evaluation analysis to the air water machine based on the real-time water production data of the air water machine, the step can realize the evaluation analysis to the water production efficiency of the air water machine, so that the production efficiency and the resource utilization condition of the air water machine can be comprehensively known, and an important reference is provided for improving the production efficiency and reducing the cost. Meanwhile, the efficiency and environmental influence optimization is carried out on the real-time water production efficiency of the air water production machine according to the environmental temperature data and the environmental humidity data of the air water production machine, so that the influence of environmental factors on the water production efficiency can be considered, and the actual water production efficiency of the air water production machine can be more accurately estimated through the optimization and adjustment of the environmental data, so that the production performance and the resource utilization efficiency of the air water production machine under different environmental conditions are improved. Then, through carrying out parameter vector conversion to air flow rate data of the air water making machine and actual water making efficiency of the air water making machine, the key of the step is that the original data can be converted into a form which can be used for subsequent analysis, and through the conversion of the parameter vector, the relation between the air flow rate and the water making efficiency can be better understood and described, and a foundation is laid for subsequent modeling and analysis. The linear regression analysis algorithm is used for carrying out flow velocity relation modeling analysis on the air flow velocity parameter vector of the air water generator based on the real-time water production efficiency parameter vector of the air water generator, and a linear relation model between the air flow velocity and the water production efficiency can be established through the model construction process, so that the air flow velocity under the corresponding water production efficiency is predicted, the establishment of the model has important significance for understanding the influence of the water production efficiency on the air flow velocity, a foundation is provided for subsequent model verification and optimization, and the air flow velocity change under different environments can be better adapted, so that a reliable basis is provided for air flow velocity control and optimization of the air water generator. Finally, by combining an air flow rate water production efficiency relation model, an air water production machine real-time water production efficiency and air flow rate data analysis of the air water production machine, deviation and uncertainty between model prediction and actual air flow rate are identified, and by utilizing a self-adaptive control algorithm to carry out working parameter adjustment analysis on the air water production machine, the working parameters of the air water production machine can be dynamically adjusted according to actual conditions so as to realize optimization and stabilization of water production efficiency, thus the self-adaptive control algorithm can adjust parameters in real time according to feedback signals and error items, the air water production machine can adapt to continuously changing working environment and conditions, and the stability and robustness of the air water production machine are improved, The adjustment strategy can effectively cope with uncertainty and variability, and ensures that the air water generator is always in an optimal working state. In addition, the corresponding air flow speed deviation condition is adaptively regulated and controlled according to the air water making machine working parameter adaptive control strategy, so that the air flow speed can be regulated and controlled in real time, the air water making machine can be kept in a preset working state by adaptively regulating and controlling the change of the flow speed error in time, the water making efficiency and the stability of the air water making machine can be improved through the regulating and controlling result, and the air water making machine can be ensured to operate efficiently under different working conditions.
Preferably, step S2 comprises the steps of:
Step S21: acquiring real-time water production data of an air water production machine;
Step S22: performing time sequence change analysis on real-time water production data of the air water production machine to obtain time sequence change trend data of water production of the air water production machine; visual drawing is carried out on time sequence change trend data of the water quantity of the air water making machine so as to generate a real-time change curve chart of the water quantity of the air water making machine;
step S23: carrying out water production rate average analysis on the real-time change curve graph of the water production of the air water production machine so as to obtain the water production rate average of the air water production machine;
Step S24: carrying out water production energy consumption statistical analysis on the real-time water production process of the air water production machine to obtain an evaluation value of water production energy consumption of the air water production machine;
step S25: performing water production efficiency evaluation analysis on the air water production machine based on the air water production machine water production average rate and the air water production machine water production energy consumption evaluation amount so as to obtain the real-time water production efficiency of the air water production machine;
Step S26: and carrying out efficiency environmental impact optimization on the real-time water production efficiency of the air water production machine according to the environmental temperature data and the environmental humidity data of the air water production machine, and obtaining the actual water production efficiency of the air water production machine.
As an embodiment of the present invention, referring to fig. 2, a detailed step flow chart of step S2 in fig. 1 is shown, in which step S2 includes the following steps:
Step S21: acquiring real-time water production data of an air water production machine;
According to the embodiment of the invention, the water production condition of the air water generator is acquired in real time by using the sensor equipment, so that the current production water quantity of the air water generator is monitored in real time and data acquisition is realized, and finally the real-time water production data of the air water generator are obtained.
Step S22: performing time sequence change analysis on real-time water production data of the air water production machine to obtain time sequence change trend data of water production of the air water production machine; visual drawing is carried out on time sequence change trend data of the water quantity of the air water making machine so as to generate a real-time change curve chart of the water quantity of the air water making machine;
According to the embodiment of the invention, the time sequence analysis is carried out on the real-time water production data of the air water production machine acquired in real time by using the methods of trend analysis, periodical analysis and the like, so that the time sequence change trend data of the water production of the air water production machine can be obtained. Then, the time sequence change trend data of the air water making machine water quantity is drawn by using a data visualization tool (such as Matplotlib, plotly and the like) so as to convert the time sequence change trend data into a chart to intuitively show the change trend of the water making quantity along with time, and finally, a real-time change curve chart of the air water making machine water quantity is generated.
Step S23: carrying out water production rate average analysis on the real-time change curve graph of the water production of the air water production machine so as to obtain the water production rate average of the air water production machine;
According to the embodiment of the invention, a change fluctuation statistical analysis method is used for carrying out statistical analysis on a drawn real-time change curve graph of the air water making mechanism water quantity, the fluctuation condition (comprising the fluctuation frequency, the fluctuation amplitude and the like) of the statistical analysis curve is used for determining the actual change point of the water making quantity change in the curve, the real-time change curve graph of the air water making mechanism water quantity obtained through combination of any two of the change points obtained through analysis is divided, so that the corresponding curve is divided into a plurality of sub-graphs, each sub-graph represents one change stage, meanwhile, the statistical calculation of the water making rate is carried out on the change curve sub-graph of each change stage to calculate the air water making mechanism water rate of each change stage, then the arithmetic average analysis method is used for calculating the air water making mechanism water rate of each change stage, so that the water making rate of each change stage is added, and the average rate is obtained by dividing the number of stages, namely the average water making rate of all change stages is obtained, and finally the air water making mechanism water average rate is obtained.
Step S24: carrying out water production energy consumption statistical analysis on the real-time water production process of the air water production machine to obtain an evaluation value of water production energy consumption of the air water production machine;
According to the embodiment of the invention, the energy consumption of the air water machine in the real-time water making process is statistically analyzed by using the energy consumption statistical analysis method, so that the energy consumption of the air water machine in the water making process, including power consumption, compressor power and the like, is statistically analyzed, the corresponding water making energy consumption estimated quantity is calculated, and finally the water making energy consumption estimated quantity of the air water machine is obtained.
Step S25: performing water production efficiency evaluation analysis on the air water production machine based on the air water production machine water production average rate and the air water production machine water production energy consumption evaluation amount so as to obtain the real-time water production efficiency of the air water production machine;
According to the embodiment of the invention, the water production efficiency of the corresponding air water production machine is calculated by carrying out statistical analysis on the water production machine water average rate and the air water production machine water energy consumption estimated quantity obtained by combining the analysis, the influence factor influencing the water production performance is determined by the influence degree obtained by the statistical analysis, and the real-time water production efficiency under different conditions is calculated by carrying out statistical analysis on the water production efficiency of the corresponding air water production machine by combining the air water production machine water rate obtained by the analysis and the influence factor between the water production efficiency and the water production performance, so that the comprehensive influence efficiency of factors such as water production quantity, energy efficiency ratio and the like on the water production performance can be reflected, and finally the real-time water production efficiency of the air water production machine is obtained.
Step S26: and carrying out efficiency environmental impact optimization on the real-time water production efficiency of the air water production machine according to the environmental temperature data and the environmental humidity data of the air water production machine, and obtaining the actual water production efficiency of the air water production machine.
According to the embodiment of the invention, the real-time water production efficiency of the air water production machine is analyzed by using an influence evaluation algorithm according to the environmental temperature data of the air water production machine and the change condition of the environmental humidity data of the air water production machine, so that the influence degree of the environmental temperature and humidity change on the water production efficiency is determined by exploring the influence relation between the environmental temperature and humidity change and the real-time water production efficiency, the real-time water production efficiency of the air water production machine is evaluated and analyzed by using an improved evaluation algorithm according to the influence degree obtained by the analysis, the potential lifting space of the water production efficiency under different environmental conditions is evaluated, the influence improvement value of the environmental temperature and humidity change on the water production efficiency is quantitatively calculated, the real-time water production efficiency of the corresponding air water production machine is improved and optimized according to the influence improvement value obtained by the quantitative calculation, and the corresponding improvement measures (including adjustment of the working parameters of the water production machine, optimization of the water production process and the like) are implemented by the air water production machine so as to adjust the operation strategy or the environment control mode of the air water production machine, the expected water production efficiency is lifted, and the air water production machine can keep high-efficient and stable under various environmental conditions, and the actual water production efficiency of the air water production machine can be obtained.
The invention firstly acquires the water production condition of the air water generator through real-time acquisition, and the key of the step is that the instant monitoring and data acquisition of the current water production of the air water generator can be realized, so that the current working state and water yield condition of the air water generator can be known through acquiring the real-time water production data, thereby providing a data basis for the subsequent analysis and optimization. Secondly, by carrying out time sequence change analysis on the real-time water production data of the air water production machine and visually drawing the time sequence change data into a real-time change curve graph, the key point of the step is that the time sequence change analysis and the visual drawing can clearly show the change trend of the air water production machine water quantity along with time, thereby providing visual data support for subsequent analysis. Meanwhile, the water making rate average analysis is carried out on the real-time change curve of the water making machine water quantity of the air to obtain the average rate of the air water making machine water, and the corresponding average water making rate can be calculated through the analysis of the real-time change curve, so that the method is beneficial to evaluating the production efficiency and performance of the air water making machine and provides a reference basis for formulating an optimization strategy. Then, through carrying out water production energy consumption statistical analysis to the real-time water production process of the air water production machine, the key of the step is that the energy consumption condition of the air water production machine in the water production process can be analyzed, so that the energy utilization efficiency of the air water production machine is estimated, reference data is provided for the subsequent analysis processing process, and meanwhile, a basis is provided for optimizing the water production efficiency. And then, the water production efficiency of the air water machine is estimated and analyzed based on the water production rate of the air water machine and the estimated water consumption of the air water machine, and the water production efficiency of the air water machine can be estimated and analyzed by comprehensively considering the water production rate and the energy consumption, so that the production efficiency and the resource utilization condition of the air water machine can be comprehensively known, and important references are provided for improving the production efficiency and reducing the cost. Finally, the efficiency and environmental influence optimization is carried out on the real-time water production efficiency of the air water production machine according to the environmental temperature data and the environmental humidity data of the air water production machine, so that the influence of environmental factors on the water production efficiency can be considered, and the actual water production efficiency of the air water production machine can be more accurately estimated through the optimization adjustment of the environmental data, so that the production performance and the resource utilization efficiency of the air water production machine under different environmental conditions are improved.
Preferably, step S23 comprises the steps of:
step S231: analyzing a change transition point of the real-time change curve graph of the water quantity of the air water making machine to obtain a change transition point of the water quantity of the air water making machine;
step S232: performing change curve segmentation processing on the real-time change curve graph of the air water production machine water quantity based on the change point of the air water production machine water quantity so as to obtain a subgraph of the change curve graph of the air water production machine water quantity in each change stage;
Step S233: carrying out water making time length statistical analysis on the air water making machine water quantity change curve subgraphs of each change stage to obtain the air water making machine water making time length of each change stage;
step S234: carrying out water making rate statistical analysis on the air water making machine water making quantity change curve subgraphs of each change stage according to the air water making machine water making time length of each change stage to obtain the air water making machine water making rate of each change stage;
step S235: and carrying out arithmetic average analysis on the water production mechanism water velocity of the air in each change stage to obtain the water production mechanism water velocity of the air.
As an embodiment of the present invention, referring to fig. 3, a detailed step flow chart of step S23 in fig. 2 is shown, in which step S23 includes the following steps:
step S231: analyzing a change transition point of the real-time change curve graph of the water quantity of the air water making machine to obtain a change transition point of the water quantity of the air water making machine;
According to the embodiment of the invention, a change fluctuation statistical analysis method is used for carrying out statistical analysis on a drawn real-time change curve graph of the air water making machine water quantity, so that fluctuation conditions (including fluctuation frequency, amplitude and the like) of a statistical analysis curve are used for revealing change characteristics of the air water making machine water quantity and fluctuation degrees of the change characteristics, a change inflection point on the real-time change curve graph of the air water making machine water quantity is scanned and marked by using an inflection point detection algorithm or a fitting curve technology, so that a key inflection point in the curve is determined, meanwhile, a detection analysis is carried out on a point with larger difference with surrounding data points on the real-time change curve graph of the air water making machine water quantity by using an anomaly detection algorithm or an anomaly statistical method, so that sudden anomaly fluctuation or mutation points are identified and found, then, the abnormal fluctuation mutation points obtained by combining the analysis are used for carrying out abnormal position matching removal on the inflection points of the change curve, positions of abnormal fluctuation points and inflection points are compared, and the positions of the abnormal fluctuation points and the inflection points are screened, namely the actual change points of the change of the water making machine water quantity after screening treatment are described by the change curve, and the change points of the water making quantity are not related to the abnormal fluctuation points, and finally, and the change point of the air water making machine water making change is obtained.
Step S232: performing change curve segmentation processing on the real-time change curve graph of the air water production machine water quantity based on the change point of the air water production machine water quantity so as to obtain a subgraph of the change curve graph of the air water production machine water quantity in each change stage;
According to the embodiment of the invention, the real-time change curve graph of the air water making mechanism water quantity is divided by combining any two of the analyzed change points of the air water making mechanism water quantity, so that the corresponding curve is divided into a plurality of sub-graphs, each sub-graph represents a change stage, the change points of the air water making mechanism water quantity are determined as the starting point and the end point of each sub-graph, and finally, the air water making mechanism water quantity change curve sub-graph of each change stage is obtained.
Step S233: carrying out water making time length statistical analysis on the air water making machine water quantity change curve subgraphs of each change stage to obtain the air water making machine water making time length of each change stage;
according to the embodiment of the invention, the water making time length of each change stage is calculated according to the starting time and the ending time of the curve by carrying out time length statistical analysis on the air water making machine water making change curve subgraphs of each change stage, and finally the air water making machine water making time length of each change stage is obtained.
Step S234: carrying out water making rate statistical analysis on the air water making machine water making quantity change curve subgraphs of each change stage according to the air water making machine water making time length of each change stage to obtain the air water making machine water making rate of each change stage;
according to the embodiment of the invention, the air water making machine water making rate of each change stage is calculated according to the water making time length of each stage and the water quantity change in the corresponding stage by analyzing the air water making machine water making time length of each change stage by using a rate statistical analysis method, and the air water making machine water making rate of each change stage is finally obtained by dividing the water quantity unit by the time unit.
Step S235: and carrying out arithmetic average analysis on the water production mechanism water velocity of the air in each change stage to obtain the water production mechanism water velocity of the air.
According to the embodiment of the invention, the water making machine water rate of each change stage is calculated by using an arithmetic average analysis method, so that the water making rate of each change stage is added, then the average rate is obtained by dividing the number of stages, namely the average water making rate of all change stages is expressed by dividing the water quantity unit by the time unit, and finally the water making machine water rate of the air is obtained.
According to the invention, the change transition point analysis is firstly carried out on the real-time change curve graph of the water quantity of the air water making machine, and the key transition point of the water quantity change of the air water making machine, namely the critical moment or trend transition point of the water quantity change, can be identified, and the important time node of the water quantity change can be accurately captured by analyzing the change trend of the curve graph, so that the basis is provided for subsequent analysis and treatment. Secondly, the change curve segmentation processing is carried out on the real-time change curve graph of the air water production machine water quantity based on the change transition point of the air water production machine water quantity, and the key of the step is that the original curve graph is segmented according to the change transition point, so that the whole curve can be segmented into a plurality of parts, the water production change curve of each part has clear characteristics and trends, and the follow-up detailed analysis and processing are facilitated. Then, by carrying out statistical analysis on the water making duration of the air water making machine water making change curve subgraphs of each change stage, the water making duration of the air water making machine in different stages can be known, and the stability and the duration of the production process of the air water making machine can be evaluated. Then, the water making rate statistical analysis is carried out on the air water making machine water making change curve subgraphs of each change stage according to the air water making machine water making time length of each change stage, and the key of the step is that the water making rate of each stage is calculated according to the water making time length, so that the water making efficiency and the change condition of the air water making machine in different stages are more accurately known. Finally, through arithmetic average analysis of the water making speed of the air water making machine in each change stage, the overall average water making speed can be obtained, which is helpful for comprehensively evaluating the overall water making efficiency and the production performance of the air water making machine, thereby providing guidance for further optimization and improvement.
Preferably, step S231 includes the steps of:
carrying out water production change fluctuation analysis on the real-time change curve graph of the water production of the air water production machine to obtain water production change fluctuation status data of the air water production machine;
According to the embodiment of the invention, the change characteristics and the fluctuation degree of the air water making machine water quantity are revealed by using a change fluctuation statistical analysis method to carry out statistical analysis on the drawn real-time change curve graph of the air water making machine water quantity, so that the fluctuation condition data of the air water making machine water quantity change fluctuation is finally obtained.
Preferably, the air water making machine water quantity real-time change curve graph is subjected to change fluctuation mode mining analysis based on air water making machine water quantity change fluctuation status data so as to obtain different water making change fluctuation mode stages in the water making change curve;
According to the embodiment of the invention, the drawn real-time change curve graph of the air water production machine water quantity is analyzed by combining the analyzed water production machine water quantity change fluctuation status data of the air water production machine by using a time sequence analysis or pattern recognition technology, so that different water production change fluctuation pattern stages are recognized and analyzed, and the change of the water production quantity is classified according to different fluctuation patterns, so that fluctuation characteristics and rules of different stages in the curve are understood more carefully, and finally, different water production change fluctuation pattern stages in the water production change curve are obtained.
Preferably, according to different water production change fluctuation mode stages in the water production change curve, carrying out change inflection point identification analysis on the real-time change curve of the air water production machine water quantity to obtain an inflection point of the air water production machine water quantity change curve;
According to the embodiment of the invention, the inflection point detection algorithm or the fitting curve technology is used for scanning and marking the change inflection point on the real-time change curve of the air water production machine water quantity by combining different water production change fluctuation mode stages in the water production change curve obtained through analysis, so that the change point of the fluctuation mode is identified to determine the key turning point in the curve, and finally the inflection point of the air water production machine water quantity change curve is obtained.
Preferably, detecting an abnormal point of the real-time change curve of the air water production machine water quantity so as to obtain an abnormal fluctuation mutation point of the air water production machine water quantity change curve;
according to the embodiment of the invention, the points with larger differences from surrounding data points on the real-time change curve graph of the water quantity of the air water making machine are detected and analyzed by using an anomaly detection algorithm or an anomaly statistics method, so that sudden anomaly fluctuation or mutation points are identified and found, the anomaly points represent the abnormal conditions, such as equipment faults, external environment changes and the like, in the operation of the air water making machine, and finally the anomaly fluctuation mutation points of the water quantity change curve of the air water making machine are obtained.
Preferably, the inflection point of the air water production system water quantity change curve is screened out in an abnormal matching way based on the abnormal fluctuation mutation point of the air water production system water quantity change curve, so as to obtain the air water production system water quantity change transition point.
According to the embodiment of the invention, the abnormal position of the inflection point of the water production change curve of the air water production mechanism is screened out by combining the abnormal fluctuation mutation point of the water production change curve of the air water production mechanism obtained through analysis, so that the positions of the abnormal fluctuation point and the inflection point are compared, and the overlapping or similar points are screened out, namely, the water production change curve inflection point after screening out treatment describes the actual change point of the water production change, and is not the point related to the abnormal fluctuation, and finally the water production change point of the air water production mechanism is obtained.
According to the invention, firstly, the fluctuation analysis of the water production change is carried out on the real-time change curve graph of the water production of the air water production machine, and the fluctuation characteristics and the fluctuation degree of the water production of the air water production machine can be disclosed by analyzing the fluctuation condition of the curve, so that the analysis is not only helpful for identifying the frequency and the amplitude of fluctuation, but also can provide statistical data about the fluctuation of the water production, such as standard deviation, variance and the like, thereby providing data support for the subsequent fluctuation mode excavation and inflection point identification. And secondly, carrying out change fluctuation mode mining analysis on the real-time change curve graph of the water quantity of the air water making machine based on the change fluctuation condition data of the water quantity of the air water making machine, so that different water making change fluctuation mode stages can be identified, and the analysis can classify the change of the water making quantity according to different fluctuation modes, thereby understanding fluctuation characteristics and rules of different stages in a curve more carefully and providing a basis for subsequent inflection point identification. Then, through the change inflection point identification analysis of the real-time change curve graph of the water production of the air water production machine according to different fluctuation mode stages of the water production change curve, key turning points in the curve are determined, inflection points in the water production change curve can be accurately captured through the identification of the change points of the fluctuation mode, the inflection points often represent important changes of the water production change trend, and the operation state and performance change of the air water production machine are helped to be understood. Then, by detecting an abnormal point of the real-time change curve graph of the water quantity of the air water making machine, sudden abnormal fluctuation or abrupt change points are found, wherein the abnormal point represents abnormal conditions in the operation of the air water making machine, such as equipment faults, external environment changes and the like. By detecting the abnormal points, problems can be found in time and corresponding measures can be taken, so that basic data guarantee is provided for subsequent inflection point abnormal elimination. Finally, the inflection point of the air water production mechanism water quantity change curve is screened out by abnormal matching based on the abnormal fluctuation mutation point of the air water production mechanism water quantity change curve, and the step aims at eliminating the interference of abnormal fluctuation on inflection point identification, so that a more reliable and accurate change transition point is obtained. By screening out points related to abnormal fluctuation in the inflection point, the accuracy and reliability of inflection point identification can be improved, so that a more reliable basis is provided for subsequent analysis and decision.
Preferably, the screening of abnormal matching of the inflection point of the air water production mechanism water quantity change curve based on the abnormal fluctuation mutation point of the air water production mechanism water quantity change curve comprises the following steps:
Carrying out abnormal fluctuation position identification analysis on abnormal fluctuation mutation points of the air water making machine water quantity change curve to obtain coordinate positions of abnormal points of the air water making machine water quantity change curve;
According to the embodiment of the invention, the coordinate positions of the abnormal fluctuation mutation points of each analyzed air water making mechanism water quantity change curve on the change curve are identified and analyzed by using the abnormal point detection method, so that the coordinate positions of the abnormal fluctuation points in the air water making mechanism water quantity change curve, namely the specific coordinate positions of the extreme value points suddenly appearing or disappearing on the curve, are accurately determined, and finally the coordinate positions of the abnormal points of each air water making mechanism water quantity curve are obtained.
Preferably, inflection point position identification analysis is carried out on the inflection points of the air water making mechanism water quantity change curve to obtain the coordinate positions of the inflection points of the air water making mechanism water quantity change curve;
According to the embodiment of the invention, the coordinate position of the analyzed change curve inflection point of the water quantity of each air water making machine is identified and analyzed by using an inflection point detection algorithm or a fitting curve technology, so that the specific coordinate position of the inflection point on the change curve, namely the coordinate position of the curve inflection point of each air water making machine, which is converted from an ascending trend or a descending trend to an opposite trend on the curve, is accurately identified, and the coordinate position of the curve inflection point of the water quantity of each air water making machine is finally obtained.
Preferably, coordinate position matching is carried out on the coordinate positions of the abnormal points of the water production curves of the air water production machines and the coordinate positions of the inflection points of the water production curves of the air water production machines so as to obtain the overlapped coordinate positions of the water production curves of the air water production machines;
The embodiment of the invention performs position matching on the coordinate positions of the abnormal points of the air water making mechanism water quantity curve on the change curve and the coordinate positions of the inflection points of the air water making mechanism water quantity curve on the change curve, which are obtained by the previous analysis, so as to compare the coordinate positions of each abnormal fluctuation point and each inflection point, find out the overlapping position between the abnormal fluctuation points and the inflection points, namely the intersection points or the adjacent positions of the abnormal fluctuation points and the inflection points on the curve, and finally obtain the overlapping coordinate position of the air water making mechanism water quantity curve.
Preferably, the inflection point of the air water making machine water yield change curve on the overlapping coordinate position of the air water making machine water yield curve is marked as an overlapping point, so that an abnormal overlapping point of the air water making machine water yield curve is obtained;
According to the embodiment of the invention, the inflection points of the air water making mechanism water quantity change curve on the overlapping coordinate position of the air water making mechanism water quantity curve are marked as corresponding overlapping points, the points represent the abnormal fluctuation and the superposition condition of the inflection points on the curve, and finally the abnormal overlapping points of the air water making mechanism water quantity curve are obtained.
Preferably, the change point of the air water production system water quantity change curve marked as the abnormal overlapping point of the air water production system water quantity curve is obtained through screening out the inflection point of the air water production system water quantity change curve.
According to the embodiment of the invention, the inflection point of the air water making mechanism water quantity change curve marked as the abnormal overlapping point of the air water making mechanism water quantity curve is screened out and removed, so that the interference of the abnormal overlapping point on the inflection point identification is eliminated, the rest of the inflection point of the air water making mechanism water quantity change curve is determined as a final change transition point, the points represent the change transition point of the air water making mechanism water quantity change, and the air water making mechanism water quantity change transition point is finally obtained.
According to the method, firstly, the abnormal fluctuation position identification analysis is carried out on the abnormal fluctuation mutation points of the air water making machine water quantity change curve, so that the coordinate positions of the abnormal fluctuation points in the air water making machine water quantity change curve are accurately determined, the mutation or abnormal fluctuation positions on the curve can be captured and accurately marked through the fine fluctuation point position analysis of the curve, and the analysis treatment process is beneficial to identifying abnormal conditions or emergencies in the air water making machine, so that accurate position information and basis are provided for subsequent processing and analysis. Secondly, through carrying out inflection point position identification analysis on the inflection point of the air water making mechanism water quantity change curve, the accurate coordinate position of the inflection point in the air water making mechanism water quantity change curve is determined, through analyzing the change trend of the curve and identifying the inflection point, the obvious turning point or inflection point in the curve can be found, the position of the turning point or inflection point is accurately marked, the analysis is helpful for capturing important change nodes in the curve, and accurate time and position information are provided for the state transition of the air water making machine. Then, coordinate position matching is carried out on the coordinate positions of the abnormal points of the water production curve of each air water production mechanism and the coordinate positions of the inflection points of the water production curve of each air water production mechanism, so that the coordinate positions of the abnormal points and the inflection points are matched to find the overlapped coordinate positions on the curve, and the overlapped positions of the abnormal points and the inflection points on the curve can be determined by comparing and matching the position information of the abnormal points and the inflection points. Finally, by marking the inflection point of the air water making mechanism water quantity change curve on the overlapping coordinate position of the air water making mechanism water quantity curve as an overlapping point so as to identify an abnormal overlapping point in the curve, the association condition of abnormal fluctuation and the inflection point in the curve can be determined, and the analysis is helpful for accurately identifying the abnormal point in the curve and carrying out corresponding treatment. Finally, the inflection point marked as the abnormal overlapping point is screened out, so that the interference of the abnormal overlapping point on the inflection point identification is eliminated, a more accurate and reliable change transition point is obtained, the accuracy and the reliability of the inflection point identification can be improved through screening out the abnormal overlapping point, and a more reliable basis is provided for analysis and prediction of the state change of the air water generator.
Preferably, step S25 comprises the steps of:
step S251: carrying out water production efficiency ratio statistical analysis on the air water production machine based on the estimated water energy consumption of the air water production machine to obtain the water production efficiency ratio of the air water production machine;
According to the embodiment of the invention, the energy consumption evaluation amount of the air water making machine and the water making amount of the air water making machine are obtained through combination analysis, so that the energy efficiency performance of the air water making machine in the water making process can be evaluated by means of statistically calculating the ratio of the water making amount to the energy consumption, the water making amount generated by the air water making machine under the given energy consumption is known, and the water making machine water energy efficiency ratio of the air water making machine is finally obtained.
Step S252: performing water production influence association mining analysis on the air water production machine based on the air water production machine water average rate and the air water production machine water energy efficiency ratio to obtain an air water production machine water speed influence association relationship and an air water production machine water energy influence association relationship;
According to the embodiment of the invention, the air water making machine is subjected to influence correlation analysis by using a correlation mining algorithm through combining the air water making machine water average speed and the air water making machine water efficiency ratio obtained by analysis, so that the influence correlation relation between the water making speed and the energy efficiency and the air water making machine water making process is mined and analyzed, the influence of the two factors on the water making machine performance is deeply understood, and finally the air water making machine water speed influence correlation relation and the air water making machine water efficiency influence correlation relation are obtained.
Step S253: performing performance influence evaluation analysis on the air water making machine according to the air water making machine water making rate influence incidence relation and the air water making machine water making efficiency influence incidence relation so as to obtain the air water making machine water making rate and the influence factors between water making efficiency and water making performance;
According to the embodiment of the invention, the water making performance of the air water making machine is evaluated and analyzed by combining the analyzed water making machine water making speed influence incidence relation and the air water making machine water energy influence incidence relation by using an influence evaluation algorithm, so that the weight or influence degree of the water making amount and the energy efficiency ratio on the performance is quantitatively determined by evaluating and analyzing the water making performance performances under different water making amounts and energy efficiency ratios, the influence factor influencing the water making performance is determined according to the analyzed influence degree, and finally the air water making machine water making speed and the influence factor between the water making efficiency and the water making performance are obtained.
Step S254: and carrying out water production efficiency statistical analysis on the air water production machine based on the water production rate of the air water production machine and the influence factor between the water production energy and the water production energy so as to obtain the real-time water production efficiency of the air water production machine.
According to the embodiment of the invention, the corresponding air water generator is subjected to statistical analysis on the water production efficiency by combining the water production rate of the air water generator and the influence factors between the water production capacity and the water production capacity, so that the real-time water production efficiency under different conditions is calculated, the comprehensive influence efficiency of factors such as water production capacity, energy efficiency ratio and the like on the water production capacity can be reflected, and the real-time water production efficiency of the air water generator is finally obtained.
According to the invention, the water production efficiency ratio of the air water production machine can be obtained by carrying out statistical analysis on the water production efficiency ratio of the air water production machine based on the water production energy consumption evaluation amount of the air water production machine, the analysis process can correlate the energy consumption with the water production efficiency so as to help evaluate the energy efficiency performance of the air water production machine in the water production process, and the water production amount generated by the air water production machine under the given energy consumption can be known by calculating the ratio of the energy consumption to the output, so that the energy efficiency performance of the air water production machine is evaluated. Secondly, carrying out water production influence association excavation analysis on the air water production machine based on the air water production machine water average speed and the air water production machine water energy ratio, wherein the analysis aims at revealing the association relation between the air water production machine water speed and the energy efficiency, so that the influence of the two factors on the water production machine performance is deeply understood. By mining the correlation between the data, the relative importance of water production rate and energy efficiency in water machine performance can be determined and guidance is provided for further performance optimization. Then, performance influence evaluation analysis is carried out on the air water making machine according to the water making machine water speed influence incidence relation and the water making machine water energy influence incidence relation so as to determine factors influencing the water making performance, the purpose of the step is to identify the influence degree of the water making speed and the energy efficiency on the water making performance and find out key factors in the factors, so that the influence of the speed and the energy efficiency on the performance can be comprehensively considered, and key strategies and directions for improving the water making performance can be determined. Finally, the water production efficiency statistical analysis is carried out on the air water production machine based on the water production rate of the air water production machine and the influence factors between the water production energy and the water production energy, and the analysis can carry out the statistical analysis on the influence factors obtained in the earlier stage and the actual water production efficiency so as to monitor and evaluate the performance of the water production machine in real time, so that the trend of performance reduction or improvement can be timely found through the real-time monitoring of the water production efficiency, and corresponding measures are adopted for adjustment and optimization so as to ensure the efficient and stable operation of the water production machine.
Preferably, step S26 includes the steps of:
step S261: according to the environmental temperature data of the air water generator and the environmental humidity data of the air water generator, analyzing the environmental influence on the real-time water production efficiency of the air water generator to obtain the influence rule data of the environmental temperature and humidity change of the air water generator on the water production efficiency;
according to the embodiment of the invention, the real-time water production efficiency of the air water production machine is analyzed by using an influence evaluation algorithm according to the environmental temperature data of the air water production machine and the change condition of the environmental humidity data of the air water production machine, so that the influence relation between the environmental temperature and humidity change and the real-time water production efficiency is explored, the specific influence rules of the temperature and the humidity on the water production efficiency are identified, for example, whether the water production efficiency is reduced due to high temperature and low humidity or not, or whether the water production efficiency is improved under the opposite condition or not, and the like, and finally the influence rule data of the environmental temperature and humidity change of the air water production machine on the water production efficiency is obtained.
Step S262: carrying out influence degree statistical analysis on influence rule data of the environmental temperature and humidity change of the air water generator on water production efficiency to obtain the influence degree of the environmental temperature and humidity change of the air water generator on the water production efficiency;
According to the embodiment of the invention, the corresponding mathematical statistical analysis method is used for carrying out statistical analysis on the influence rule data of the environmental temperature and humidity change of the air water generator, which is obtained through analysis, on the water generation efficiency, wherein the statistical analysis comprises the steps of calculating correlation coefficients, making scatter diagrams, box diagrams and the like, so as to know the relation among the correlation and the change degree of the correlation, determining the influence degree of the environmental temperature and humidity change on the water generation efficiency, and finally obtaining the influence degree of the environmental temperature and humidity change of the air water generator on the water generation efficiency.
Step S263: performing efficiency improvement evaluation analysis on the real-time water production efficiency of the air water production machine based on the influence degree of the environmental temperature and humidity change of the air water production machine on the water production efficiency so as to obtain an influence optimization improvement coefficient of the environmental temperature and humidity change of the air water production machine on the water production efficiency;
According to the embodiment of the invention, the water production efficiency under different temperature and humidity conditions is compared by combining the influence degree of the environmental temperature and humidity change of the air water production machine on the water production efficiency, and the real-time water production efficiency of the air water production machine is evaluated and analyzed by using an improved evaluation algorithm so as to evaluate the potential lifting space of the water production efficiency under different environmental conditions, and meanwhile, the influence improvement value of the environmental temperature and humidity change on the water production efficiency is quantitatively calculated, and finally, the influence optimization improvement coefficient of the environmental temperature and humidity change of the air water production machine on the water production efficiency is obtained.
Step S264: and optimizing efficiency improvement on the real-time water production efficiency of the air water production machine according to the influence optimization improvement coefficient of the environmental temperature and humidity change of the air water production machine on the water production efficiency, so as to obtain the actual water production efficiency of the air water production machine.
According to the embodiment of the invention, the real-time water production efficiency of the corresponding air water production machine is improved and optimized by optimizing the improvement coefficient according to the influence of the environmental temperature and humidity change of the air water production machine on the water production efficiency, which is obtained through quantitative calculation, so that the running strategy or the environmental control mode of the air water production machine is adjusted by implementing corresponding improvement measures (including adjusting the working parameters of the water production machine, optimizing the water production process and the like), the expected water production efficiency is improved, the air water production machine can maintain the high-efficiency stable water production performance under various environmental conditions, and the actual water production efficiency of the air water production machine is finally obtained.
According to the invention, the environmental impact analysis is carried out on the real-time water production efficiency of the air water production machine according to the environmental temperature data and the environmental humidity data of the air water production machine, the analysis process aims at revealing the influence rule of the environmental condition change on the water production efficiency, and the specific influence trend of the temperature and the humidity on the water production efficiency can be identified by collecting and analyzing the data under different environmental conditions. For example, whether high temperature and low humidity result in a decrease in water production efficiency, or vice versa, whether water production efficiency is improved, etc., which data are critical to understanding the performance of the water machine in different operating environments. And secondly, the influence degree statistical analysis is carried out on the influence rule data of the environmental temperature and humidity change of the air water generator on the water production efficiency, so that the influence degree of the temperature and humidity change on the water production efficiency can be quantified, the efficiency loss or the promotion degree under various environmental conditions can be determined, and the quantitative analysis is helpful for determining which environmental factors have the greatest influence on the water production efficiency, thereby providing a specific basis for subsequent efficiency improvement and optimization. Then, through carrying out efficiency improvement evaluation analysis on the real-time water production efficiency of the air water production machine based on the influence degree of the environmental temperature and humidity change of the air water production machine on the water production efficiency, potential lifting space of the water production efficiency under different environmental conditions can be evaluated, and the influence optimization improvement coefficients of the environmental temperature and humidity change on the water production efficiency are calculated, wherein the coefficients reflect how to improve the water production efficiency of the air water production machine by adjusting and optimizing the environmental conditions in actual operation, so that energy consumption or water production is reduced. Finally, the efficiency improvement optimization is carried out on the real-time water production efficiency of the air water production machine by optimizing the improvement coefficient according to the influence of the environmental temperature and humidity change of the air water production machine on the water production efficiency, the purpose of the step is to implement specific efficiency improvement measures, and the expected water production efficiency improvement is achieved by adjusting the operation strategy or the environmental control mode of the air water production machine. Through optimization, the air water generator can be ensured to keep high-efficiency and stable water production performance under various environmental conditions, so that the actual water production efficiency and the overall operation performance of the air water generator are improved.
Preferably, step S3 comprises the steps of:
Step S31: performing parameter vector conversion on air flow rate data of the air water making machine and actual water making efficiency of the air water making machine to obtain an air flow rate parameter vector of the air water making machine and a real-time water making efficiency parameter vector of the air water making machine;
according to the embodiment of the invention, the air flow rate data of the air water generator and the actual water production efficiency of the air water generator are subjected to parameter division according to a certain time interval and converted into a vector form, so that the collected air flow rate data and water production efficiency data are arranged into the vector form according to a certain rule and standard, the collected air flow rate data and the collected water production efficiency data are ensured to be on the same scale, meanwhile, deviation caused by different scales is avoided in subsequent analysis, and finally, the air flow rate parameter vector of the air water generator and the real-time water production efficiency parameter vector of the air water generator are obtained.
Step S32: based on the real-time water production efficiency parameter vector of the air water production machine, performing flow velocity relation model training on the air flow velocity parameter vector of the air water production machine by using a linear regression analysis algorithm to obtain an initial linear regression relation model of air flow velocity;
According to the embodiment of the invention, the model training is carried out on the air flow velocity parameter vector of the air water generator by using a linear regression analysis algorithm aiming at the real-time water production efficiency parameter vector of the air water generator, so that the linear relation between the water production efficiency and the air flow velocity is researched, the real-time water production efficiency parameter vector is used as an independent variable, the air flow velocity parameter vector is used as a dependent variable, meanwhile, the linear relation between the air flow velocity parameter vector and the air flow velocity is described by minimizing residual square and fitting a straight line, and finally, the initial linear regression relation model of the air flow velocity is obtained through training.
Step S33: and performing model verification, evaluation and optimization on the initial linear regression relation model of the air flow velocity to generate a relation model of the air flow velocity water production efficiency.
According to the embodiment of the invention, the trained initial linear regression relation model of the air flow rate is subjected to model verification by using a corresponding test set and combining a cross verification technology, so that the generalization capability of the model on new data is verified, the accuracy and reliability of the model are evaluated, meanwhile, the model is optimized according to a verification result, the super-parameters of the model are adjusted to improve the linear association relation between the predicted air flow rate and the water production efficiency, and finally the air flow rate water production efficiency relation model is generated.
According to the invention, the parameter vector conversion is firstly carried out on the air flow velocity data of the air water making machine and the actual water making efficiency of the air water making machine, the key of the step is that the original data can be converted into a form which can be used for subsequent analysis, and the relation between the air flow velocity and the water making efficiency can be better understood and described through the conversion of the parameter vector, so that a foundation is laid for subsequent modeling and analysis. Then, through carrying out flow velocity relation model training on the air flow velocity parameter vector of the air water machine by using a linear regression analysis algorithm based on the real-time water production efficiency parameter vector of the air water machine, a preliminary linear relation model between the air flow velocity and the water production efficiency can be established through the model training process, so that the air flow velocity under the corresponding water production efficiency is predicted, and the establishment of the model has important significance for understanding the influence of the water production efficiency on the air flow velocity and provides a basis for subsequent model verification and optimization. Finally, through model verification, evaluation and optimization of the initial linear regression relation model of the air flow velocity, the main purpose of the step is to find problems of the model and optimize the model through verification and evaluation of the initially established relation model, so that the accuracy and reliability of the model are improved. Through the optimization process, the relation between the air flow rate and the water production efficiency can be better described, so that a reliable basis is provided for controlling and optimizing the air flow rate of the air water production machine.
Preferably, step S31 comprises the steps of:
Analyzing time sequence change of air flow velocity data of the air water making machine and actual water making efficiency of the air water making machine to obtain time sequence change trend data of the air flow velocity of the air water making machine and time sequence change trend data of the water making efficiency of the air water making machine;
According to the embodiment of the invention, the time sequence statistical analysis method or the data visualization tool is used for carrying out change analysis on the air flow rate data of the air water generator and the actual water production efficiency of the air water generator so as to analyze and reveal the change trend of the air flow rate and the water production efficiency of the air water generator in different time periods, and meanwhile, the change trend of the air flow rate and the water production efficiency is determined, and finally, the time sequence change trend data of the air flow rate of the air water generator and the time sequence change trend data of the water production efficiency of the air water generator are obtained.
Preferably, the air flow rate sampling interval design is carried out on the air flow rate data of the air water generator based on the air flow rate time sequence variation trend data of the air water generator, so as to obtain the air flow rate sampling interval of the air water generator; performing flow rate sampling and arithmetic average analysis on air flow rate data of the air water generator according to the air flow rate sampling time intervals of the air water generator so as to obtain average air flow rates of the air water generator at all the flow rate sampling time intervals;
According to the embodiment of the invention, the corresponding air flow rate data of the air water heater is analyzed according to the time sequence variation trend data of the air flow rate of the air water heater, so that the variation characteristics of the air flow rate of the air water heater are analyzed, the sampling time interval length of the air flow rate is designed according to the variation characteristics obtained by analysis, the time interval of the corresponding length is determined, and the variation of the air flow rate is accurately described, so that the air flow rate sampling time interval of the air water heater is obtained. Then, sampling air flow rate data of the air water generator by using the designed air flow rate sampling time intervals of the air water generator, and carrying out arithmetic average analysis so as to average the air flow rate collected in each sampling time interval, thereby obtaining average air flow rate in a corresponding time period, and finally obtaining the average air flow rate of the air water generator in each flow rate sampling time interval.
Preferably, the design of an efficiency sampling interval is carried out on the actual water production efficiency of the air water production machine based on the time sequence variation trend data of the water production efficiency of the air water production machine, so as to obtain the sampling interval of the water production efficiency of the air water production machine; according to the sampling time intervals of the water production efficiency of the air water production machine, carrying out efficiency sampling and arithmetic average analysis on the actual water production efficiency of the air water production machine so as to obtain the average water production efficiency of the air water production machine in each sampling time interval of the efficiency;
According to the embodiment of the invention, the corresponding actual water production efficiency of the air water production machine is analyzed according to the time sequence change trend data of the water production efficiency of the air water production machine, so that the change characteristics of the water production efficiency of the air water production machine are analyzed, the sampling time interval length of the water production efficiency is designed according to the change characteristics obtained by analysis, the time interval of the corresponding length is determined to accurately describe the change of the water production efficiency, and the sampling time interval of the water production efficiency of the air water production machine is obtained. Then, sampling the water production efficiency of the air water production machine by using the designed sampling time intervals of the water production efficiency of the air water production machine, and carrying out arithmetic average analysis so as to average the water production efficiency collected in each sampling time interval, thereby obtaining the average water production efficiency in the corresponding time period, and finally obtaining the average water production efficiency of the air water production machine with each efficiency sampling time interval.
Preferably, the parameter vector conversion is carried out on the average air flow velocity of the air water generator at each flow velocity sampling time interval and the average water production efficiency of the air water generator at each efficiency sampling time interval respectively so as to obtain the air flow velocity parameter vector of the air water generator and the real-time water production efficiency parameter vector of the air water generator.
According to the embodiment of the invention, the average air flow rate of the air water generator at each flow rate sampling time interval and the average water production efficiency of the air water generator at each efficiency sampling time interval are subjected to vector conversion according to the sequence of the time sequence, so that the average air flow rate and the average water production efficiency before and after the corresponding time sequence are respectively converted into vector forms, further processing and analysis are facilitated, and finally the air flow rate parameter vector of the air water generator and the real-time water production efficiency parameter vector of the air water generator are obtained.
According to the invention, the time sequence change analysis is carried out on the air flow rate data of the air water generator and the actual water production efficiency of the air water generator, so that the change trend of the air flow rate and the water production efficiency of the air water generator in different time periods can be revealed, the dynamic change of the performance of the air water generator can be understood, and a foundation is provided for subsequent analysis and optimization. For example, it can be found whether there is a certain correlation or trend between the air flow rate and the water production efficiency, and their law of variation over different time periods. Secondly, by designing flow rate sampling intervals based on time sequence variation trend data of the air flow rate of the air water generator and sampling and arithmetic average analyzing the air flow rate data of the air water generator, the average air flow rate of each flow rate sampling time interval can be obtained, and the aim of the step is to extract the air flow rate data of the corresponding time sequence interval so as to facilitate subsequent parameter conversion and modeling analysis. Through arithmetic average analysis, noise and fluctuation in the data can be eliminated, more stable and reliable air flow velocity data can be obtained, and reliable input is provided for subsequent processing procedures. Then, through carrying out efficiency sampling interval design on time sequence variation trend data of water efficiency of the air water making machine, sampling and arithmetic average analysis on actual water making efficiency, average water making efficiency of each efficiency sampling time interval can be obtained, and likewise, the step aims at extracting water making efficiency data of corresponding time sequence intervals so as to facilitate subsequent parameter conversion and modeling analysis, and through sampling and analysis on the water making efficiency, performance of the air water making machine in different time periods can be known, and basis is provided for subsequent parameter vector conversion processes. Finally, through carrying out parameter vector conversion on the average air flow rate of each flow rate sampling time interval and the average water production efficiency of each efficiency sampling time interval, an air flow rate parameter vector and a real-time water production efficiency parameter vector of the air water production machine can be obtained, and the key point of the step is that the analyzed and processed data can be converted into a form of the parameter vector so as to facilitate subsequent modeling and analysis, and the performance characteristics of the air water production machine can be better described through the conversion of the parameter vector, thereby providing a basis for further analysis and optimization.
Preferably, step S4 comprises the steps of:
step S41: inputting the real-time water production efficiency of the air water production machine into an air flow rate water production efficiency relation model to conduct air flow rate model prediction, so as to obtain air flow rate model prediction data of the air water production machine;
according to the embodiment of the invention, the real-time water production efficiency of the air water production machine before being optimized is input into the constructed air flow rate water production efficiency relation model to conduct model prediction of the corresponding air flow rate, so that the air flow rate under the corresponding water production efficiency is deduced based on the existing real-time water production efficiency data and the linear relation model, and finally the air flow rate model prediction data of the air water production machine are obtained.
Step S42: performing flow speed error evaluation analysis on air flow speed data of the air water making machine and air flow speed model prediction data of the air water making machine to obtain an air flow speed error item to be adjusted of the air water making machine;
According to the embodiment of the invention, the air flow velocity data measured by the air water generator in the actual operation process and the air flow velocity model prediction data are compared and subjected to error analysis by using an error statistical analysis method, so that the difference between the real-time flow velocity and the model prediction is compared, the deviation and the uncertainty between the model prediction and the actual air flow velocity are identified, and finally the air flow velocity to-be-adjusted error item of the air water generator is obtained.
Step S43: based on an air flow rate to-be-adjusted error item of the air water making machine, carrying out working parameter adjustment analysis on the air water making machine by utilizing an adaptive control algorithm so as to generate an adaptive control strategy for working parameters of the air water making machine;
According to the embodiment of the invention, the corresponding working parameters of the air water generator are adjusted and analyzed by using a corresponding self-adaptive control algorithm (comprising a PID control, a Model Predictive Control (MPC) and other self-adaptive control methods) in combination with the air flow rate error term of the air water generator, so that the water generation efficiency is improved, different air flow rate conditions are adapted, corresponding strategies for adjusting the working parameters of the air water generator are dynamically generated according to the change condition of the air flow rate error term, namely, the parameter adjustment scheme which should be adopted under different error conditions is determined, so that the air water generator can adapt to the continuously changed working environment and conditions, and finally, the self-adaptive control strategies for the working parameters of the air water generator are generated, including the control strategies for adjusting the fan rotation speed, increasing the moisture absorption film area, heating temperature and the like.
Step S44: and carrying out self-adaptive regulation and control treatment on the air flow rate to-be-regulated error item of the air water generator according to the self-adaptive control strategy of the working parameters of the air water generator to obtain the air flow rate regulation and control result of the air water generator.
According to the embodiment of the invention, the generated self-adaptive control strategy of the working parameters of the air water heater is used for carrying out self-adaptive regulation and control on the corresponding error items to be regulated of the air flow rate of the air water heater, so that the working parameters of the air water heater are dynamically regulated according to the control strategy, the optimal control of the air flow rate is realized, the air water heater can be ensured to operate efficiently under different working conditions, and finally the regulation and control result of the air flow rate of the air water heater is obtained.
According to the invention, the real-time water production efficiency of the air water production machine is input into the constructed air flow rate water production efficiency relation model to conduct air flow rate model prediction, the air flow rate under the corresponding water production efficiency can be deduced based on the existing data and model, the prediction is beneficial to real-time monitoring and predicting of the performance of the air water production machine, and guidance is provided for subsequent optimization and adjustment. Through prediction, potential change of the air flow rate can be found in time, and corresponding measures are adopted to control and adjust the air flow rate so as to ensure stability and optimization of water production efficiency. Secondly, through carrying out flow rate error evaluation analysis on air flow rate data of the air water generator and air flow rate model prediction data, the difference between the real-time flow rate and model prediction can be compared, so that the accuracy and reliability of the model are evaluated. Then, the working parameters of the air water generator can be dynamically adjusted according to actual conditions by utilizing a self-adaptive control algorithm to carry out working parameter adjustment analysis on the air water generator based on the air flow rate to-be-adjusted error item of the air water generator so as to realize optimization and stability of water generation efficiency, and the self-adaptive control algorithm can adjust parameters in real time according to feedback signals and the error item, so that the air water generator can adapt to continuously changing working environment and conditions, stability and robustness of the air water generator are improved, uncertainty and variability can be effectively dealt with by using the adjustment strategy, and the air water generator is ensured to be always in an optimal working state. Finally, the air flow rate to-be-regulated error item of the air water generator is subjected to self-adaptive regulation and control according to the working parameter self-adaptive control strategy of the air water generator, so that the real-time regulation and control of the air flow rate can be realized, the change of the flow rate error can be responded in time through self-adaptive regulation and control, the air water generator can be kept in a preset working state, the regulation and control result can improve the water generation efficiency and the stability of the air water generator, and the air water generator can be ensured to operate efficiently under different working conditions.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. The air flow rate self-adaptive control modeling method of the air water maker is characterized by comprising the following steps of:
Step S1: the air flow rate sensor and the environmental parameter sensor are distributed around the air water generator, and the air flow rate sensor and the environmental parameter sensor are used for collecting and processing environmental parameters of the air water generator so as to obtain air flow rate data of the air water generator, environmental temperature data of the air water generator and environmental humidity data of the air water generator;
step S2: acquiring real-time water production data of the air water production machine, and performing water production efficiency evaluation analysis on the air water production machine based on the real-time water production data of the air water production machine so as to obtain the real-time water production efficiency of the air water production machine; according to the environmental temperature data of the air water generator and the environmental humidity data of the air water generator, optimizing the efficiency and environmental influence of the air water generator on the real-time water production efficiency of the air water generator, and obtaining the actual water production efficiency of the air water generator;
step S3: performing parameter vector conversion on air flow rate data of the air water making machine and actual water making efficiency of the air water making machine to obtain an air flow rate parameter vector of the air water making machine and a real-time water making efficiency parameter vector of the air water making machine; performing flow velocity relation modeling analysis on the air flow velocity parameter vector of the air water generator based on the real-time water production efficiency parameter vector of the air water generator so as to generate an air flow velocity water production efficiency relation model;
Step S4: based on the air flow rate water production efficiency relation model, the real-time water production efficiency of the air water production machine and the air flow rate data of the air water production machine, carrying out working parameter adjustment analysis on the air water production machine by utilizing an adaptive control algorithm so as to generate an adaptive control strategy for working parameters of the air water production machine; and carrying out self-adaptive regulation and control treatment according to the self-adaptive control strategy of the working parameters of the air water making machine to obtain the air flow rate regulation and control result of the air water making machine.
2. The modeling method for adaptive control of air flow rate of air-to-water machine according to claim 1, wherein step S2 comprises the steps of:
Step S21: acquiring real-time water production data of an air water production machine;
Step S22: performing time sequence change analysis on real-time water production data of the air water production machine to obtain time sequence change trend data of water production of the air water production machine; visual drawing is carried out on time sequence change trend data of the water quantity of the air water making machine so as to generate a real-time change curve chart of the water quantity of the air water making machine;
step S23: carrying out water production rate average analysis on the real-time change curve graph of the water production of the air water production machine so as to obtain the water production rate average of the air water production machine;
Step S24: carrying out water production energy consumption statistical analysis on the real-time water production process of the air water production machine to obtain an evaluation value of water production energy consumption of the air water production machine;
step S25: performing water production efficiency evaluation analysis on the air water production machine based on the air water production machine water production average rate and the air water production machine water production energy consumption evaluation amount so as to obtain the real-time water production efficiency of the air water production machine;
Step S26: and carrying out efficiency environmental impact optimization on the real-time water production efficiency of the air water production machine according to the environmental temperature data and the environmental humidity data of the air water production machine, and obtaining the actual water production efficiency of the air water production machine.
3. The air flow rate adaptive control modeling method of an air water machine according to claim 2, wherein step S23 includes the steps of:
step S231: analyzing a change transition point of the real-time change curve graph of the water quantity of the air water making machine to obtain a change transition point of the water quantity of the air water making machine;
step S232: performing change curve segmentation processing on the real-time change curve graph of the air water production machine water quantity based on the change point of the air water production machine water quantity so as to obtain a subgraph of the change curve graph of the air water production machine water quantity in each change stage;
Step S233: carrying out water making time length statistical analysis on the air water making machine water quantity change curve subgraphs of each change stage to obtain the air water making machine water making time length of each change stage;
step S234: carrying out water making rate statistical analysis on the air water making machine water making quantity change curve subgraphs of each change stage according to the air water making machine water making time length of each change stage to obtain the air water making machine water making rate of each change stage;
step S235: and carrying out arithmetic average analysis on the water production mechanism water velocity of the air in each change stage to obtain the water production mechanism water velocity of the air.
4. The air flow rate adaptive control modeling method of an air water generator according to claim 3, wherein step S231 comprises the steps of:
carrying out water production change fluctuation analysis on the real-time change curve graph of the water production of the air water production machine to obtain water production change fluctuation status data of the air water production machine;
Performing change fluctuation mode mining analysis on the real-time change curve graph of the water quantity of the air water making machine based on the water quantity change fluctuation status data of the air water making machine so as to obtain different water making change fluctuation mode stages in the water making change curve;
According to different water production change fluctuation mode stages in the water production change curve, carrying out change inflection point identification analysis on the real-time change curve of the water production of the air water production machine to obtain a change inflection point of the water production change curve of the air water production machine;
Detecting abnormal points on the real-time change curve graph of the water yield of the air water production machine so as to obtain abnormal fluctuation mutation points of the change curve of the water yield of the air water production machine;
And (3) screening out abnormal matching of inflection points of the air water making mechanism water quantity change curve based on abnormal fluctuation mutation points of the air water making mechanism water quantity change curve to obtain water making mechanism water quantity change transition points.
5. The modeling method for adaptive control of air flow rate of an air water generator according to claim 4, wherein the screening out abnormal matching of inflection points of the air water generator change curve based on abnormal fluctuation mutation points of the air water generator change curve comprises the following steps:
Carrying out abnormal fluctuation position identification analysis on abnormal fluctuation mutation points of the air water making machine water quantity change curve to obtain coordinate positions of abnormal points of the air water making machine water quantity change curve;
performing inflection point position identification analysis on the inflection points of the air water making machine water quantity change curve to obtain the coordinate positions of the inflection points of the air water making machine water quantity change curve;
coordinate position matching is carried out on the coordinate positions of the abnormal points of the water production curves of the air water production machines and the coordinate positions of inflection points of the water production curves of the air water production machines so as to obtain overlapped coordinate positions of the water production curves of the air water production machines;
The inflection point of the air water making machine water yield change curve on the overlapping coordinate position of the air water making machine water yield curve is marked as an overlapping point, and an abnormal overlapping point of the air water making machine water yield curve is obtained;
And screening out the inflection point of the air water making mechanism water quantity change curve marked as the abnormal overlapping point of the air water making mechanism water quantity curve to obtain the air water making mechanism water quantity change transition point.
6. The air flow rate adaptive control modeling method of an air water machine according to claim 2, wherein step S25 includes the steps of:
step S251: carrying out water production efficiency ratio statistical analysis on the air water production machine based on the estimated water energy consumption of the air water production machine to obtain the water production efficiency ratio of the air water production machine;
Step S252: performing water production influence association mining analysis on the air water production machine based on the air water production machine water average rate and the air water production machine water energy efficiency ratio to obtain an air water production machine water speed influence association relationship and an air water production machine water energy influence association relationship;
step S253: performing performance influence evaluation analysis on the air water making machine according to the air water making machine water making rate influence incidence relation and the air water making machine water making efficiency influence incidence relation so as to obtain the air water making machine water making rate and the influence factors between water making efficiency and water making performance;
step S254: and carrying out water production efficiency statistical analysis on the air water production machine based on the water production rate of the air water production machine and the influence factor between the water production energy and the water production energy so as to obtain the real-time water production efficiency of the air water production machine.
7. The air flow rate adaptive control modeling method of an air water machine according to claim 2, wherein step S26 includes the steps of:
step S261: according to the environmental temperature data of the air water generator and the environmental humidity data of the air water generator, analyzing the environmental influence on the real-time water production efficiency of the air water generator to obtain the influence rule data of the environmental temperature and humidity change of the air water generator on the water production efficiency;
step S262: carrying out influence degree statistical analysis on influence rule data of the environmental temperature and humidity change of the air water generator on water production efficiency to obtain the influence degree of the environmental temperature and humidity change of the air water generator on the water production efficiency;
Step S263: performing efficiency improvement evaluation analysis on the real-time water production efficiency of the air water production machine based on the influence degree of the environmental temperature and humidity change of the air water production machine on the water production efficiency so as to obtain an influence optimization improvement coefficient of the environmental temperature and humidity change of the air water production machine on the water production efficiency;
Step S264: and optimizing efficiency improvement on the real-time water production efficiency of the air water production machine according to the influence optimization improvement coefficient of the environmental temperature and humidity change of the air water production machine on the water production efficiency, so as to obtain the actual water production efficiency of the air water production machine.
8. The modeling method for adaptive control of air flow rate of air-to-water machine according to claim 1, wherein step S3 comprises the steps of:
Step S31: performing parameter vector conversion on air flow rate data of the air water making machine and actual water making efficiency of the air water making machine to obtain an air flow rate parameter vector of the air water making machine and a real-time water making efficiency parameter vector of the air water making machine;
step S32: based on the real-time water production efficiency parameter vector of the air water production machine, performing flow velocity relation model training on the air flow velocity parameter vector of the air water production machine by using a linear regression analysis algorithm to obtain an initial linear regression relation model of air flow velocity;
step S33: and performing model verification, evaluation and optimization on the initial linear regression relation model of the air flow velocity to generate a relation model of the air flow velocity water production efficiency.
9. The method for modeling adaptive control of air flow rate of an air-water machine according to claim 8, wherein step S31 comprises the steps of:
Analyzing time sequence change of air flow velocity data of the air water making machine and actual water making efficiency of the air water making machine to obtain time sequence change trend data of the air flow velocity of the air water making machine and time sequence change trend data of the water making efficiency of the air water making machine;
performing flow rate sampling interval design on air flow rate data of the air water generator based on air flow rate time sequence variation trend data of the air water generator to obtain air flow rate sampling intervals of the air water generator; performing flow rate sampling and arithmetic average analysis on air flow rate data of the air water generator according to the air flow rate sampling time intervals of the air water generator so as to obtain average air flow rates of the air water generator at all the flow rate sampling time intervals;
the method comprises the steps that efficiency sampling interval design is conducted on actual water production efficiency of an air water production machine based on time sequence change trend data of the water production efficiency of the air water production machine, and the sampling interval of the water production efficiency of the air water production machine is obtained; according to the sampling time intervals of the water production efficiency of the air water production machine, carrying out efficiency sampling and arithmetic average analysis on the actual water production efficiency of the air water production machine so as to obtain the average water production efficiency of the air water production machine in each sampling time interval of the efficiency;
and respectively carrying out parameter vector conversion on the average air flow velocity of the air water making machine at each flow velocity sampling time interval and the average water making efficiency of the air water making machine at each efficiency sampling time interval so as to obtain an air flow velocity parameter vector of the air water making machine and a real-time water making efficiency parameter vector of the air water making machine.
10. The modeling method for adaptive control of air flow rate of air-to-water machine according to claim 1, wherein step S4 comprises the steps of:
step S41: inputting the real-time water production efficiency of the air water production machine into an air flow rate water production efficiency relation model to conduct air flow rate model prediction, so as to obtain air flow rate model prediction data of the air water production machine;
Step S42: performing flow speed error evaluation analysis on air flow speed data of the air water making machine and air flow speed model prediction data of the air water making machine to obtain an air flow speed error item to be adjusted of the air water making machine;
Step S43: based on an air flow rate to-be-adjusted error item of the air water making machine, carrying out working parameter adjustment analysis on the air water making machine by utilizing an adaptive control algorithm so as to generate an adaptive control strategy for working parameters of the air water making machine;
step S44: and carrying out self-adaptive regulation and control treatment on the air flow rate to-be-regulated error item of the air water generator according to the self-adaptive control strategy of the working parameters of the air water generator to obtain the air flow rate regulation and control result of the air water generator.
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