CN118313728A - Intelligent chemical engineering quality detection system and method - Google Patents
Intelligent chemical engineering quality detection system and method Download PDFInfo
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Abstract
The invention provides an intelligent engineering quality detection system and method, and relates to the field of engineering detection. The intelligent engineering quality detection system comprises a sensor module, wherein the sensor module comprises a temperature sensor, a humidity sensor, a pressure sensor, a noise sensor and a displacement sensor and is used for collecting various data of an engineering site in real time; the data acquisition and transmission module is in charge of transmitting the data acquired by the sensor to the next step; the central processing unit adopts a high-performance processor and a data processing algorithm to analyze and process the received data in real time; and the control module is used for carrying out corresponding control operation according to the acquisition and processing results. By setting the early warning threshold value, an alarm prompt can be automatically sent once an abnormal condition is detected, and meanwhile, historical data is stored and analyzed, so that a reference basis is provided for engineering quality evaluation, and the whole structure is flexible and can be customized and expanded according to engineering requirements.
Description
Technical Field
The invention relates to the technical field of engineering detection, in particular to an intelligent engineering quality detection system and method.
Background
The engineering quality detection refers to the process of monitoring, evaluating and checking various quality indexes of engineering projects in the design, construction and use processes so as to ensure that the engineering quality reaches the specified standard and requirement. The engineering quality detection aims at finding and solving engineering quality problems, guaranteeing safety, reliability and durability of engineering projects, and gradually developing safety detection means of building engineering along with development of technology, wherein the engineering quality intelligent detection mainly realizes quality monitoring, analysis and management of the engineering projects by utilizing technical means such as artificial intelligence, big data, cloud computing and the like, the engineering projects have a large number of quality inspection standards related to engineering quality in the process of standing, construction and completion acceptance, the analysis of the big data often depends on knowledge literacy of quality inspection unit staff, the problem of slow analysis efficiency exists, the data information of the whole process of the engineering projects cannot be displayed, the existing means for analyzing and processing the big data through big data analysis refers to a technical means for processing the big data, and the aim at extracting valuable information from the big complex data.
However, the existing intelligent process quality detection system still has some defects and places to be improved in the actual use process, the technology of the existing intelligent system is still in a development stage, certain limitations exist, meanwhile, the existing intelligent system is difficult to adapt to diversified demands, in certain cases, artificial experience and judgment are significant, the intelligent system cannot completely replace an artificial role, the artificial role is needed to be combined with the intelligent system, and the problem cannot be timely reported when abnormality is found in the detection process, so that the intelligent process quality detection system and method are provided by the person skilled in the art to solve the problem in the background art.
Disclosure of Invention
(One) solving the technical problems
Aiming at the defects of the prior art, the invention provides an intelligent chemical engineering quality detection system and method, which solve the problems that the existing detection system has certain limitation and can not completely replace manual judgment.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme: an intelligent process quality detection system comprising:
The sensor module comprises a temperature sensor, a humidity sensor, a pressure sensor, a noise sensor and a displacement sensor and is used for collecting various data of an engineering site in real time;
The data acquisition and transmission module is in charge of transmitting the data acquired by the sensor to the next step and ensuring the real-time performance and accuracy of the data;
The central processing unit is used for carrying out real-time analysis and processing on the received data by adopting a high-performance processor and a data processing algorithm to generate an engineering quality detection report;
the control module is used for carrying out corresponding control operation according to the acquisition and processing results and providing a friendly operation interface;
The alarm module is used for setting a threshold value in advance, and if the abnormal condition of the engineering quality is detected in the detection process, the alarm module exceeds the preset threshold value, and the system automatically sends out an alarm to inform related personnel for processing;
and the data storage and analysis module is used for storing and analyzing the historical data and providing a reference basis for engineering quality evaluation.
Preferably, the specific operation steps of the data acquisition and transmission module are as follows:
Firstly, determining monitoring parameters and sensor selection, wherein the parameters to be monitored, including temperature, humidity, pressure, noise and displacement, need to be determined firstly, and selecting a proper sensor according to the monitoring parameters to ensure that the performance of the sensor meets the monitoring requirements;
secondly, deploying and installing the sensors, wherein the selected sensors are deployed and installed according to design requirements, so that the proper positions of the sensors are ensured, and data can be accurately acquired;
thirdly, selecting a proper data acquisition device by the data acquisition device, and processing and transmitting the data acquired by the sensor;
a fourth step of selecting a data transmission mode, namely selecting a proper data transmission mode according to a monitoring scene and requirements, selecting a corresponding transmission mode according to a specific monitoring scene, wherein different transmission modes have different characteristics and applicable scenes, and selecting according to actual conditions;
The fifth step, the data transmission system is deployed, wherein the deployment of the data transmission system comprises the installation of transmission equipment and the configuration work of a network environment, so that the data transmission system can stably and efficiently transmit the acquired data;
and sixthly, carrying out data acquisition and transmission testing after the system deployment is completed, so as to ensure that the system can normally operate and accurately transmit data.
Preferably, the central processing unit further comprises data storage, processing and analysis functions.
Preferably, the control module further comprises a function of graphically displaying engineering quality data, alarm prompts and parameter settings, wherein the interactive software comprises PC end software, mobile APP and a Web page.
Preferably, the central processing unit comprises feature extraction, model establishment and model training, wherein key features are extracted from the preprocessed data for subsequent analysis and judgment, a quality detection model is established by using machine learning and deep learning technologies, a large amount of sample data are used for training the model, and the performance of the model is optimized.
Preferably, the model training in the central processing unit may employ one or more of decision trees, random forests, logistic regression, and linear regression.
The detection method of the intelligent industrial quality detection system comprises the following steps:
S1, data acquisition, namely acquiring related data including the form, the size and the mechanical property of an engineering structure by using various sensors and monitoring equipment;
S2, data transmission, namely transmitting the acquired data to a central processing unit in real time, so as to ensure the integrity and timeliness of the data;
s3, preprocessing data, namely cleaning, screening and de-duplication processing is carried out on the acquired data, and abnormal values and interference data are removed;
S4, extracting features, namely extracting key features from the preprocessed data for subsequent analysis and judgment;
s5, establishing a model, and establishing a quality detection model by using a machine learning and deep learning technology;
s6, training the model, namely training the model by using a large amount of sample data, and optimizing the performance of the model;
S7, monitoring engineering in real time through equipment of a sensor to obtain real-time data;
s8, data analysis, namely inputting real-time data into a training model for analysis and judgment;
S9, evaluating the quality, namely evaluating the engineering quality according to the output result of the model, and determining whether a quality problem exists or not;
S10, performing fault diagnosis, if quality problems are found, performing fault diagnosis, and determining the reasons and positions of the problems;
s11, early warning notification is sent out timely to inform relevant personnel of engineering quality problems;
S12, report generation and data storage are carried out, a detailed quality detection report is generated, and detection data and results are stored, so that subsequent inquiry and analysis are facilitated.
(III) beneficial effects
The invention provides an intelligent chemical engineering quality detection system and method. The beneficial effects are as follows:
1. According to the invention, various data of an engineering site can be monitored in real time, abnormal conditions can be found in time, meanwhile, the data are intelligently analyzed and processed by utilizing an artificial intelligence technology, and the accuracy and the efficiency of detection are improved.
2. According to the invention, through setting the early warning threshold value, an alarm prompt can be automatically sent out once an abnormal condition is detected, and meanwhile, historical data is stored and analyzed, so that a reference basis is provided for engineering quality evaluation, and the whole structure is flexible and can be customized and expanded according to engineering requirements.
Drawings
FIG. 1 is a schematic diagram of the overall process of the present invention;
FIG. 2 is a schematic diagram showing a specific classification of the sensor according to the present invention;
FIG. 3 is a schematic diagram showing steps of a data acquisition and transmission module according to the present invention;
Fig. 4 is a flow chart of the cpu according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
as shown in fig. 1-4, an embodiment of the present invention provides an intelligent chemical quality detection system, comprising:
The sensor module comprises a temperature sensor, a humidity sensor, a pressure sensor, a noise sensor and a displacement sensor and is used for collecting various data of an engineering site in real time;
The data acquisition and transmission module is in charge of transmitting the data acquired by the sensor to the next step and ensuring the real-time performance and accuracy of the data;
The central processing unit is used for carrying out real-time analysis and processing on the received data by adopting a high-performance processor and a data processing algorithm to generate an engineering quality detection report;
the control module is used for carrying out corresponding control operation according to the acquisition and processing results and providing a friendly operation interface;
The alarm module is used for setting a threshold value in advance, and if the abnormal condition of the engineering quality is detected in the detection process, the alarm module exceeds the preset threshold value, and the system automatically sends out an alarm to inform related personnel for processing;
and the data storage and analysis module is used for storing and analyzing the historical data and providing a reference basis for engineering quality evaluation.
The specific operation steps of the data acquisition and transmission module are as follows:
Firstly, determining monitoring parameters and sensor selection, wherein the parameters to be monitored, including temperature, humidity, pressure, noise and displacement, need to be determined firstly, and selecting a proper sensor according to the monitoring parameters to ensure that the performance of the sensor meets the monitoring requirements;
secondly, deploying and installing the sensors, wherein the selected sensors are deployed and installed according to design requirements, so that the proper positions of the sensors are ensured, and data can be accurately acquired;
thirdly, selecting a proper data acquisition device by the data acquisition device, and processing and transmitting the data acquired by the sensor;
a fourth step of selecting a data transmission mode, namely selecting a proper data transmission mode according to a monitoring scene and requirements, selecting a corresponding transmission mode according to a specific monitoring scene, wherein different transmission modes have different characteristics and applicable scenes, and selecting according to actual conditions;
The fifth step, the data transmission system is deployed, wherein the deployment of the data transmission system comprises the installation of transmission equipment and the configuration work of a network environment, so that the data transmission system can stably and efficiently transmit the acquired data;
and sixthly, carrying out data acquisition and transmission testing after the system deployment is completed, so as to ensure that the system can normally operate and accurately transmit data.
The central processing unit further comprises data storage, processing and analysis functions, the control module further comprises functions of graphically displaying engineering quality data, alarming prompts and parameter setting, the interactive software comprises PC end software, mobile APP and Web pages, the central processing unit comprises feature extraction, model building and model training, key features are extracted from preprocessed data and used for subsequent analysis and judgment, a quality detection model is built by using machine learning and deep learning technologies, a large amount of sample data is used for training the model, performance of the model is optimized, and model training in the central processing unit can adopt one or more of decision trees, random forests, logistic regression and linear regression.
The detection method of the intelligent industrial quality detection system comprises the following steps:
S1, data acquisition, namely acquiring related data including the form, the size and the mechanical property of an engineering structure by using various sensors and monitoring equipment;
S2, data transmission, namely transmitting the acquired data to a central processing unit in real time, so as to ensure the integrity and timeliness of the data;
s3, preprocessing data, namely cleaning, screening and de-duplication processing is carried out on the acquired data, and abnormal values and interference data are removed;
S4, extracting features, namely extracting key features from the preprocessed data for subsequent analysis and judgment;
s5, establishing a model, and establishing a quality detection model by using a machine learning and deep learning technology;
s6, training the model, namely training the model by using a large amount of sample data, and optimizing the performance of the model;
S7, monitoring engineering in real time through equipment of a sensor to obtain real-time data;
s8, data analysis, namely inputting real-time data into a training model for analysis and judgment;
S9, evaluating the quality, namely evaluating the engineering quality according to the output result of the model, and determining whether a quality problem exists or not;
S10, performing fault diagnosis, if quality problems are found, performing fault diagnosis, and determining the reasons and positions of the problems;
s11, early warning notification is sent out timely to inform relevant personnel of engineering quality problems;
S12, report generation and data storage are carried out, a detailed quality detection report is generated, and detection data and results are stored, so that subsequent inquiry and analysis are facilitated.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. Intelligent industrial quality detection system, its characterized in that: comprising the following steps:
The sensor module comprises a temperature sensor, a humidity sensor, a pressure sensor, a noise sensor and a displacement sensor and is used for collecting various data of an engineering site in real time;
The data acquisition and transmission module is in charge of transmitting the data acquired by the sensor to the next step and ensuring the real-time performance and accuracy of the data;
The central processing unit is used for carrying out real-time analysis and processing on the received data by adopting a high-performance processor and a data processing algorithm to generate an engineering quality detection report;
the control module is used for carrying out corresponding control operation according to the acquisition and processing results and providing a friendly operation interface;
The alarm module is used for setting a threshold value in advance, and if the abnormal condition of the engineering quality is detected in the detection process, the alarm module exceeds the preset threshold value, and the system automatically sends out an alarm to inform related personnel for processing;
and the data storage and analysis module is used for storing and analyzing the historical data and providing a reference basis for engineering quality evaluation.
2. The intelligent process quality detection system of claim 1, wherein: the specific operation steps of the data acquisition and transmission module are as follows:
Firstly, determining monitoring parameters and sensor selection, wherein the parameters to be monitored, including temperature, humidity, pressure, noise and displacement, need to be determined firstly, and selecting a proper sensor according to the monitoring parameters to ensure that the performance of the sensor meets the monitoring requirements;
secondly, deploying and installing the sensors, wherein the selected sensors are deployed and installed according to design requirements, so that the proper positions of the sensors are ensured, and data can be accurately acquired;
thirdly, selecting a proper data acquisition device by the data acquisition device, and processing and transmitting the data acquired by the sensor;
a fourth step of selecting a data transmission mode, namely selecting a proper data transmission mode according to a monitoring scene and requirements, selecting a corresponding transmission mode according to a specific monitoring scene, wherein different transmission modes have different characteristics and applicable scenes, and selecting according to actual conditions;
The fifth step, the data transmission system is deployed, wherein the deployment of the data transmission system comprises the installation of transmission equipment and the configuration work of a network environment, so that the data transmission system can stably and efficiently transmit the acquired data;
and sixthly, carrying out data acquisition and transmission testing after the system deployment is completed, so as to ensure that the system can normally operate and accurately transmit data.
3. The intelligent process quality detection system of claim 1, wherein: the central processing unit further comprises data storage, processing and analysis functions.
4. The intelligent process quality detection system of claim 1, wherein: the control module also comprises functions of graphically displaying engineering quality data, alarm prompt and parameter setting, wherein the interactive software comprises PC end software, mobile APP and a Web page.
5. The intelligent process quality detection system of claim 1, wherein: the central processing unit comprises feature extraction, model establishment and model training, key features are extracted from the preprocessed data and used for subsequent analysis and judgment, a quality detection model is established by utilizing machine learning and deep learning technologies, a large amount of sample data are used for training the model, and the performance of the model is optimized.
6. The intelligent process quality inspection system according to any one of claims 1 to 5, wherein: model training in the central processing unit may employ one or more of decision trees, random forests, logistic regression, and linear regression.
7. The detection method of the intelligent chemical engineering quality detection system is characterized by comprising the following steps of: the method comprises the following steps:
S1, data acquisition, namely acquiring related data including the form, the size and the mechanical property of an engineering structure by using various sensors and monitoring equipment;
S2, data transmission, namely transmitting the acquired data to a central processing unit in real time, so as to ensure the integrity and timeliness of the data;
s3, preprocessing data, namely cleaning, screening and de-duplication processing is carried out on the acquired data, and abnormal values and interference data are removed;
S4, extracting features, namely extracting key features from the preprocessed data for subsequent analysis and judgment;
s5, establishing a model, and establishing a quality detection model by using a machine learning and deep learning technology;
s6, training the model, namely training the model by using a large amount of sample data, and optimizing the performance of the model;
S7, monitoring engineering in real time through equipment of a sensor to obtain real-time data;
s8, data analysis, namely inputting real-time data into a training model for analysis and judgment;
S9, evaluating the quality, namely evaluating the engineering quality according to the output result of the model, and determining whether a quality problem exists or not;
S10, performing fault diagnosis, if quality problems are found, performing fault diagnosis, and determining the reasons and positions of the problems;
s11, early warning notification is sent out timely to inform relevant personnel of engineering quality problems;
S12, report generation and data storage are carried out, a detailed quality detection report is generated, and detection data and results are stored, so that subsequent inquiry and analysis are facilitated.
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