CN118628095B - Self-adaptive formulation method, device and medium for storage tank maintenance strategy - Google Patents
Self-adaptive formulation method, device and medium for storage tank maintenance strategy Download PDFInfo
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Abstract
The application discloses a self-adaptive formulation method, equipment and medium of a storage tank maintenance strategy, wherein the method comprises the following steps: acquiring the operation parameters of the storage tank, and evaluating the health influence degree of the storage tank by the operation parameters of the storage tank to obtain a health influence sequence of the storage tank; based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation; determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence; determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the health short-board influence parameters and the current health state of the storage tank; based on preset historical maintenance data, determining a historical maintenance strategy, and iterating the real-time maintenance strategy of the storage tank to the historical maintenance strategy to obtain a current storage tank maintenance strategy. The method solves the technical problems that the timeliness of the formulation of the storage tank maintenance strategy is poor, the potential abnormality is easy to be overlooked, and the matching degree of the storage tank maintenance strategy and the actual demand is low.
Description
Technical Field
The present application relates to the field of storage tank maintenance technologies, and in particular, to a method, an apparatus, and a medium for adaptively formulating a storage tank maintenance policy.
Background
In the chemical industry, a storage tank is used as a key device, and the stable operation of the storage tank is directly related to the production efficiency and the safety. During actual operation, the tank may experience various anomalies such as leakage, corrosion, material aging, pressure fluctuations, etc., due to reduced system safety during its use. If the abnormal conditions cannot be maintained regularly in time, environmental pollution, equipment damage and even casualties can be caused due to the fact that the safety degree of the storage tank system is reduced.
In the existing storage tank maintenance strategy, the strategy that the storage tank needs to be maintained is judged through the acquired storage tank parameters. Existing tank maintenance strategies mostly rely on periodic manual inspection and planned maintenance tasks, which have significant delays in time. In the operation process of the storage tank, the state parameters (such as pressure, temperature, liquid level, corrosion condition and the like) of the storage tank are continuously changed, and the changes cannot be captured in time by regular inspection, so that potential safety hazards are difficult to discover and treat in time. In the prior art, for the formulation of the storage tank maintenance strategy, the influence factors are easily ignored in the formulation process, and the problem of insufficient matching degree exists.
Disclosure of Invention
The embodiment of the application provides a self-adaptive formulation method, equipment and medium for a storage tank maintenance strategy, which solve the technical problems that the formulation of the storage tank maintenance strategy in the prior art is poor in timeliness, potential abnormality is easy to be overlooked, and the matching degree of the storage tank maintenance strategy and actual requirements is low.
In a first aspect, an embodiment of the present application provides a method for adaptively formulating a maintenance policy of a storage tank, where the method includes: acquiring the operation parameters of the storage tank, and evaluating the health influence degree of the storage tank by the operation parameters of the storage tank to obtain a health influence sequence of the storage tank; based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation; determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence; determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the influence parameters of the health short plates of the storage tank and the current health state of the storage tank; based on preset historical maintenance data, determining a historical maintenance strategy through storage tank maintenance inertia processing, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy.
In one implementation of the present application, the storage tank operation parameters are evaluated for a storage tank health impact to obtain a storage tank health impact sequence, which specifically includes: performing storage tank operation parameter pretreatment on the storage tank operation parameters to obtain impurity-removed storage tank operation parameter data; wherein, the operation parameter data of the impurity removal storage tank comprises: valve tightness, storage tank pressure, structural variables, storage tank temperature, and seam tightness; carrying out storage tank abnormal obvious degree discrimination on the impurity-removed storage tank operation parameter data so as to determine a storage tank operation parameter obvious degree sequence; performing abnormal state simulation on the storage tank operation parameters with the obviously lower than a preset threshold in the storage tank operation parameter obviously sequence to determine a first storage tank health influence sequence; wherein, the abnormal state simulation of the storage tank comprises: quantitatively simulating the time of the abnormal state of the storage tank and quantitatively simulating the abnormal degree of the abnormal state of the storage tank; performing conventional abnormal influence sequencing on the storage tank operation parameters with the clarity higher than a preset threshold in the storage tank operation parameter clarity sequence to determine a second storage tank health influence sequence; a tank health impact sequence is determined based on the first tank health impact sequence and the second tank health impact sequence.
In one implementation of the application, based on the storage tank health influence sequence, the storage tank health short-board influence parameters are determined through storage tank operation single parameter accumulation, and the method specifically comprises the following steps: counting the quantity of the storage tank influence factors on the storage tank health influence sequence, and determining the upper limit of the storage tank influence factors corresponding to the storage tank health influence sequence according to the quantity of the storage tank influence factors obtained by counting the quantity of the storage tank influence factors; based on the upper limit of the storage tank influence factors, obtaining a storage tank abnormal upper limit accumulation sequence by carrying out abnormal upper limit accumulation on each storage tank influence factor; and determining the influence parameters of the short health plates of the storage tank according to the accumulation sequence of the abnormal upper limit of the storage tank.
In one implementation of the present application, determining a current health status of a tank through tank health assessment according to a tank health impact sequence specifically includes: acquiring historical operation data of the storage tank, and determining current operation data of the storage tank according to the historical operation data of the storage tank; wherein, the current operation data of the storage tank comprises: tank run time, tank storage class, tank component replacement data; determining a matching sequence of current operation data of the storage tank through storage demand analysis of the storage tank based on storage category of the storage tank and storage tank health influence sequence; matching the tank run time with the matching sequence to determine a first tank health coefficient; determining current data of the storage tank component according to the replacement data of the storage tank component; matching the current data of the storage tank component with the matching sequence, and carrying out weighted average on the matching result to obtain a second storage tank health coefficient; the current state of health of the tank is determined based on the first tank health coefficient and the second tank health coefficient.
In one implementation of the application, based on the tank health short-circuit influence parameter and the current health state of the tank, the real-time maintenance strategy of the tank is determined through analysis of the historical operation parameters of the tank, and the method specifically comprises the following steps: setting the influence parameters of the short health plates of the storage tank as storage tank health variable data, and performing curve fitting according to the current health condition of the storage tank through the storage tank health variable data to obtain a real-time maintenance scheme of the storage tank; based on the current health state of the storage tank, determining a real-time storage tank upgrading scheme through storage tank upgrading analysis; according to the real-time maintenance scheme of the storage tank and a real-time upgrade scheme of the storage tank, and determining a real-time maintenance strategy of the storage tank.
In one implementation of the present application, determining a history maintenance policy based on preset history maintenance data through storage tank maintenance inertia processing specifically includes: classifying the historical maintenance data into abnormal states of the storage tank, and determining a maintenance inertia strategy of the storage tank through processing inertia matching of the abnormal states of the storage tank based on classification results of the abnormal states of the storage tank; and integrating data of the storage tank maintenance inertia strategy to determine a historical maintenance strategy.
In one implementation of the present application, after iterating the real-time maintenance strategy of the storage tank to the preset historical maintenance strategy to obtain the current storage tank maintenance strategy, the method further includes: based on the current storage tank maintenance strategy, the storage tank is maintained to obtain storage tank state update data; performing tank health assessment on the tank status update data to determine current tank update status data; and determining a storage tank pre-maintenance strategy according to the current update state data of the storage tank.
In one implementation of the present application, after determining the tank pre-maintenance policy based on the current updated status data of the tank, the method further comprises: based on a storage tank pre-maintenance strategy, a storage tank pre-maintenance plan is formulated; and carrying out storage tank pre-maintenance state change evaluation on the storage tank pre-maintenance plan, and determining an event change threshold of the storage tank pre-maintenance plan according to an evaluation result of the storage tank pre-maintenance state change evaluation.
In a second aspect, an embodiment of the present application further provides an apparatus for adaptively formulating a maintenance policy of a storage tank, where the apparatus includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to: acquiring the operation parameters of the storage tank, and evaluating the health influence degree of the storage tank by the operation parameters of the storage tank to obtain a health influence sequence of the storage tank; based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation; determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence; determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the influence parameters of the health short plates of the storage tank and the current health state of the storage tank; based on preset historical maintenance data, determining a historical maintenance strategy through storage tank maintenance inertia processing, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy.
In a third aspect, an embodiment of the present application further provides a nonvolatile computer storage medium storing computer executable instructions for adaptively formulating a tank maintenance policy, where the computer executable instructions are configured to: acquiring the operation parameters of the storage tank, and evaluating the health influence degree of the storage tank by the operation parameters of the storage tank to obtain a health influence sequence of the storage tank; based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation; determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence; determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the influence parameters of the health short plates of the storage tank and the current health state of the storage tank; based on preset historical maintenance data, determining a historical maintenance strategy through storage tank maintenance inertia processing, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy.
The embodiment of the application provides a self-adaptive formulation method, equipment and medium of a storage tank maintenance strategy, which are characterized in that an influence factor influencing the performance of a storage tank in the storage process of the storage tank is analyzed, a storage tank health influence sequence is determined, an abnormal upper limit analysis is carried out on the influence factor of the storage tank to obtain a storage tank health short-circuit influence parameter, and the health state analysis of the storage tank is carried out on the basis of the data; the method solves the technical problems that in the prior art, the timeliness of the formulation of the storage tank maintenance strategy is poor, the potential abnormality is easy to be overlooked, and the matching degree of the storage tank maintenance strategy and the actual demand is low; the method realizes the real-time monitoring of the health state of the storage tank and the immediate automatic formulation of the maintenance strategy of the storage tank, improves the timeliness and the matching degree of the formulation of the maintenance plan of the storage tank and can meet the adaptation degree of the formulation of the strategy through iteration in the updating process of the maintenance strategy of the storage tank.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a method for adaptively formulating a maintenance strategy for a storage tank according to an embodiment of the present application;
fig. 2 is a schematic diagram of an internal structure of an adaptive formulation device for a storage tank maintenance policy according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The embodiment of the application provides a self-adaptive formulation method, equipment and medium of a storage tank maintenance strategy, which are characterized in that an influence factor influencing the performance of a storage tank in the storage process of the storage tank is analyzed, a storage tank health influence sequence is determined, an abnormal upper limit analysis is carried out on the influence factor of the storage tank to obtain a storage tank health short-circuit influence parameter, and the health state analysis of the storage tank is carried out on the basis of the data; the method solves the technical problems that in the prior art, the timeliness of the formulation of the storage tank maintenance strategy is poor, the potential abnormality is easy to be overlooked, and the matching degree of the storage tank maintenance strategy and the actual demand is low; the method realizes the real-time monitoring of the health state of the storage tank and the immediate automatic formulation of the maintenance strategy of the storage tank, improves the timeliness and the matching degree of the formulation of the maintenance plan of the storage tank and can meet the adaptation degree of the formulation of the strategy through iteration in the updating process of the maintenance strategy of the storage tank.
The following describes the technical scheme provided by the embodiment of the application in detail through the attached drawings.
Fig. 1 is a flowchart of a method for adaptively formulating a maintenance strategy for a storage tank according to an embodiment of the present application. As shown in fig. 1, the method for adaptively formulating the maintenance strategy of the storage tank provided by the embodiment of the application specifically includes the following steps:
And 101, acquiring the operation parameters of the storage tank, and evaluating the health influence degree of the storage tank by the operation parameters of the storage tank to obtain a health influence sequence of the storage tank.
The method specifically comprises the following steps: performing storage tank operation parameter pretreatment on the storage tank operation parameters to obtain impurity-removed storage tank operation parameter data; wherein, the operation parameter data of the impurity removal storage tank comprises: valve tightness, storage tank pressure, structural variables, storage tank temperature, and seam tightness; carrying out storage tank abnormal obvious degree discrimination on the impurity-removed storage tank operation parameter data so as to determine a storage tank operation parameter obvious degree sequence; performing abnormal state simulation on the storage tank operation parameters with the obviously lower than a preset threshold in the storage tank operation parameter obviously sequence to determine a first storage tank health influence sequence; wherein, the abnormal state simulation of the storage tank comprises: quantitatively simulating the time of the abnormal state of the storage tank and quantitatively simulating the abnormal degree of the abnormal state of the storage tank; performing conventional abnormal influence sequencing on the storage tank operation parameters with the clarity higher than a preset threshold in the storage tank operation parameter clarity sequence to determine a second storage tank health influence sequence; a tank health impact sequence is determined based on the first tank health impact sequence and the second tank health impact sequence.
According to the application, the storage tank operation parameters are subjected to storage tank health influence degree evaluation to obtain the storage tank health influence sequence, and the abnormal state simulation is performed on the storage tank operation parameters, so that the distribution of the influence degree of the self health degree of the storage tank under the effects of chemical storage, external condition influence and the loss of the storage tank self-parts is realized.
In the present embodiment, the following example 1 is used for explanation in detail.
Example 1: and acquiring the operation parameters of the storage tank based on a sensor arranged on the storage tank system, and uploading the parameter data to the storage tank health analysis module through the Internet of things.
Firstly, preprocessing the operation parameters of a storage tank; wherein, the pretreatment of the operation parameters of the storage tank comprises: data cleaning, outlier detection and removal and data standardization.
The operation parameter data of the impurity removal storage tank comprises: valve tightness, tank pressure, structural variables, tank temperature, and seam tightness.
For the tightness of the valve, a pipeline valve, a breather valve and the like are used as nodes where the storage tank is easy to fail or leak, and the positions and inflection points are difficult to detect or the manual detection is easy to generate negligence due to higher concealment degree of the positions and inflection points.
The pressure of the storage tank can be monitored in real time through a precise pressure sensor arranged in the storage tank or in a key pipeline.
The storage tank structure configuration variable can carry out millimeter level monitoring to the storage tank body through installing big dipper monitoring facilities, except that the deformation appears in the tank body, also can monitor the condition that deposit and little displacement appear in the tank body.
The temperature of the storage tank can also be monitored in real time through a temperature sensor arranged in the storage tank.
For seam tightness, the flange interface, the sealing means, and the can weld are easily ignored and difficult to directly monitor.
Therefore, the abnormal clarity of the storage tank needs to be judged according to the positions of the corresponding parts of the parameters, the storage tank main body is used for three-dimensional modeling, and the clarity judgment is carried out according to the three-dimensional model of the storage tank main body.
According to the current model of the storage tank system, a threshold value is comprehensively determined according to the covered area occupation ratio of the components, the space size of the joint of the components and the size of the components, the storage tank components are judged according to the threshold value, whether the storage tank components are in the current state or in the state after replacement and upgrading, the component higher than the threshold value is high in obviously degree, and corresponds to a part which is not easy to be ignored in the actual working environment; otherwise, the part which is easy to be ignored in the actual working environment is the part which is easy to be ignored.
And carrying out abnormal state simulation on the storage tank operation parameters with the clarity lower than a preset threshold in the storage tank operation parameter clarity sequence so as to determine a first storage tank health influence sequence.
And regarding the operation parameters corresponding to the flange interface which is positioned at the inner side of the inflection point of the pipeline and has the shielding rate larger than the preset threshold value, the partial area of the welding line of the tank body, the small sealing device and the like as the operation parameters corresponding to the parts which are easy to be ignored in the actual working environment.
For abnormal state simulation, the abnormal start (the condition that the valve just loosens, a small amount of leakage and the like) of each part is taken as the simulated abnormal state of the storage tank, and the abnormal degree and the health influence of the storage tank under the corresponding abnormal state are obtained. And sequencing from heavy to light according to the abnormality degree and the health state of the storage tank, and determining a first storage tank health influence sequence.
Similarly, since the abnormal state is easy to find and has a daily work inspection process, the normal abnormal influence sorting is performed on the storage tank operation parameters with the clarity higher than the preset threshold value in the storage tank operation parameter clarity sequence, and the second storage tank health influence sequence is still determined according to the sorting from heavy to light of the abnormal degree and the health state of the storage tank in the abnormal simulation.
The tank health impact sequence characterizes a magnitude order of the extent of impact of the tank operating parameters corresponding to the tank components on the tank health.
Step 102, based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation.
The method specifically comprises the following steps: counting the quantity of the storage tank influence factors on the storage tank health influence sequence, and determining the upper limit of the storage tank influence factors corresponding to the storage tank health influence sequence according to the quantity of the storage tank influence factors obtained by counting the quantity of the storage tank influence factors; based on the upper limit of the storage tank influence factors, obtaining a storage tank abnormal upper limit accumulation sequence by carrying out abnormal upper limit accumulation on each storage tank influence factor; and determining the influence parameters of the short health plates of the storage tank according to the accumulation sequence of the abnormal upper limit of the storage tank.
According to the application, through accumulation of single parameters of the operation of the storage tank, the influence parameters of the short plates of the health of the storage tank are determined, so that the upper limit analysis of the abnormality of the corresponding part in the operation of the storage tank is realized, the quantification of the abnormal state assessment of the storage tank part is realized, and a data basis can be provided for the prediction of the abnormal occurrence of the storage tank.
In the present embodiment, the following example 2 is used for explanation in detail.
Example 2: because the number of the required parts is different in the operation process of the storage tank system, the abnormal state of the storage tank can be caused by the fact that the storage tank parts are aged and the like to a certain extent needs to be judged.
And counting the storage tank components corresponding to each storage tank operation parameter according to the sequence of the storage tank health influence sequences. In the petroleum storage tank A, there are 2 liquid inlet and outlet valves, 3 safety valves, 16 flange interfaces and the like; the number of influencing factors of the liquid inlet and outlet valves is 2, and so on.
According to the number of the storage tank influence factors obtained by counting the number of the storage tank influence factors, determining the upper limit of the storage tank influence factors corresponding to the storage tank health influence sequence specifically comprises the following steps: based on the number of the storage tank influence factors, an upper limit of the storage tank influence factors is determined through storage tank health critical analysis.
The critical analysis of the health of the storage tank is that the storage tank is in a critical abnormal state when the storage tank component corresponding to the influence factor is in the critical abnormal state. This state is an inherent property of the tank components and the tank body, which is quantitatively represented by the tank health analysis.
And the abnormal upper limit accumulation is carried out on each storage tank influence factor, and the obtained storage tank abnormal upper limit accumulation sequence is the abnormal accumulation of one storage tank influence factor, namely the aging, the abrasion and the like of the corresponding storage tank component are simulated. As a result of the simulation against a single factor, the tank was characterized as being about to be abnormal (other components default to no problem) when the component reached a critical condition.
And among all storage tank operation parameters acquired by the sensor network of the Internet of things, the higher the risk level is, the easier the abnormal upper limit is broken through, and the risk level is used as a storage tank health short-board influence parameter.
Through the technical scheme, the evaluation logic of the overall health state of the storage tank and the influence parameters of the short plates of the storage tank can be determined, and the current state of the storage tank can be evaluated.
Step 103, determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence.
The method specifically comprises the following steps: acquiring historical operation data of the storage tank, and determining current operation data of the storage tank according to the historical operation data of the storage tank; wherein, the current operation data of the storage tank comprises: tank run time, tank storage class, tank component replacement data; determining a matching sequence of current operation data of the storage tank through storage demand analysis of the storage tank based on storage category of the storage tank and storage tank health influence sequence; matching the tank run time with the matching sequence to determine a first tank health coefficient; determining current data of the storage tank component according to the replacement data of the storage tank component; matching the current data of the storage tank component with the matching sequence, and carrying out weighted average on the matching result to obtain a second storage tank health coefficient; the current state of health of the tank is determined based on the first tank health coefficient and the second tank health coefficient.
According to the storage tank health influence sequence, the current health state of the storage tank is determined through storage tank health evaluation, and the current real-time state of the storage tank is evaluated through the combination of the Internet of things sensor network and the storage tank health evaluation method.
In the present embodiment, the following example 3 is explained in detail.
Example 3: the operation time of the storage tank is divided into the total operation time of the storage tank; the storage class of the storage tank is the type of storage chemical material of the storage tank, and generally comprises: explosives, drugs, corrosives, oxidants, and the like; the tank component replacement data is a time node corresponding to the tank component updated for the tank.
The operation time of the storage tank is matched with the health influence degree of the corresponding time period in the matching sequence, and the sealing performance and the overall strength of the joint position of the storage tank are in direct proportion to the storage time, namely, the longer the storage time is in the storage process of chemical substances with the same corrosiveness, the worse the strength and the sealing performance of the storage tank are. Matching and evaluating according to the storage type, and determining the health coefficient of the first storage tank
At a certain operating time, the tank storing the corrosive acid raw material is usually in a moderate corrosion state, and the first tank health coefficient is 0.6 (1 is the best state, and 0 is the worst state).
Determining current data of the storage tank component according to the replacement data of the storage tank component; and matching the current data of the storage tank component with the matching sequence, and carrying out weighted average on the matching result to obtain a second storage tank health coefficient.
Some seal and flange connection in the tank have been replaced recently due to a slight leak, indicating that the component is currently in good condition but has previously been problematic.
The state of the seal is matched to the relevant item in the matching sequence and the case of other replaced components is considered. And under the condition that the states of other components are good, carrying out weighted average on the matching results of all the related components to obtain the second storage tank health coefficient of 0.85.
Finally, the current state of health of the tank is determined by a simple averaging method based on the first tank health coefficient (0.6) and the second tank health coefficient (0.85). The current state of health coefficient of the tank is (0.6 + 0.85)/2=0.725, indicating that the tank is in a moderately upward state of health, but the potential impact of storing corrosive materials on its health needs to be noted.
And 104, determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the short-circuit influence parameters of the storage tank health and the current health state of the storage tank.
The method specifically comprises the following steps: setting the influence parameters of the short health plates of the storage tank as storage tank health variable data, and performing curve fitting according to the current health condition of the storage tank through the storage tank health variable data to obtain a real-time maintenance scheme of the storage tank; based on the current health state of the storage tank, determining a real-time storage tank upgrading scheme through storage tank upgrading analysis; according to the real-time maintenance scheme of the storage tank and a real-time upgrade scheme of the storage tank, and determining a real-time maintenance strategy of the storage tank.
According to the method, based on the influence parameters of the short plate of the storage tank health and the current health state of the storage tank, the real-time maintenance strategy of the storage tank is determined through analysis of the historical operation parameters of the storage tank, so that the automatic formulation of the maintenance strategy of the storage tank according to the real-time operation parameter data of the storage tank is realized, the formulation efficiency of the maintenance plan of the storage tank is improved, and the starting time of the maintenance plan of the storage tank is shortened.
In the present embodiment, the following example 4 is explained in detail.
Example 4: fitting the current health condition of the storage tank and the storage tank health variable data through a neural network, wherein the storage tank health variable data is the storage tank health short-board data.
The current health condition of the storage tank is used as a starting point of a curve, the influence of the short-circuit data of the health of the storage tank is used as an influence factor influencing the health of the storage tank, the time is the horizontal axis of the curve function, and the vertical axis is the health condition (changing with time) of the curve function.
Because the overall change condition of the health of the storage tank needs to be judged, the storage tank health short-plate data can also change along with the change of the storage tank health state, and at the moment, a curve corresponding to the health short-plate data of another storage tank needs to be subjected to curve fitting.
The fitting result is factor information (i.e., an upper limit value) corresponding to a tank component that requires maintenance at a first time in the current abnormal state of the tank.
For the upgrading scheme of the storage tank, comprehensive analysis is required according to the performance requirement and the actual operation requirement of the storage tank, and the corresponding part for upgrading the storage tank and the specific upgrading condition of the corresponding part are determined.
Step 105, determining a historical maintenance strategy through storage tank maintenance inertia processing based on preset historical maintenance data, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy.
The method specifically comprises the following steps: classifying the historical maintenance data into abnormal states of the storage tank, and determining a maintenance inertia strategy of the storage tank through processing inertia matching of the abnormal states of the storage tank based on classification results of the abnormal states of the storage tank; and integrating data of the storage tank maintenance inertia strategy to determine a historical maintenance strategy.
After iterating the real-time maintenance strategy of the storage tank to the preset historical maintenance strategy to obtain the current storage tank maintenance strategy, the method further comprises: based on the current storage tank maintenance strategy, the storage tank is maintained to obtain storage tank state update data; performing tank health assessment on the tank status update data to determine current tank update status data; and determining a storage tank pre-maintenance strategy according to the current update state data of the storage tank.
After determining the tank pre-maintenance strategy based on the current updated status data of the tank, the method further comprises: based on a storage tank pre-maintenance strategy, a storage tank pre-maintenance plan is formulated; and carrying out storage tank pre-maintenance state change evaluation on the storage tank pre-maintenance plan, and determining an event change threshold of the storage tank pre-maintenance plan according to an evaluation result of the storage tank pre-maintenance state change evaluation.
According to the application, based on preset historical maintenance data, the historical maintenance strategy is determined through storage tank maintenance inertia processing, and the real-time maintenance strategy of the storage tank is iterated to the historical maintenance strategy to obtain the current storage tank maintenance strategy, and the storage tank pre-maintenance strategy is determined according to the current storage tank maintenance strategy, so that the self-adaption of the storage tank maintenance strategy is realized, and the efficiency and the matching degree of the formulation of the storage tank maintenance strategy are improved.
In the examples of the present application, the following example 5 is explained in detail.
Example 5: the storage tank maintenance records of the past five years are derived, including maintenance date, storage tank number, fault type (such as leakage, corrosion, pressure abnormality, etc.), maintenance measures, maintenance effect, etc.
Data cleaning: duplicate records, erroneous data (e.g., date format errors, encoding inconsistencies, etc.) are removed using a data cleansing tool, and missing values are filled (e.g., using averages, median, or predictions based on other relevant fields).
Characteristics associated with abnormal conditions of the tank, such as type of failure, frequency of occurrence of failure, duration of failure, environmental factors (e.g., temperature, humidity, salinity), etc., are selected from the cleaned data.
The features are trained using machine learning algorithms (e.g., decision trees, random forests, or gradient-lifting trees) to classify the abnormal state of the tank. During the training process, the data set is divided into a training set and a testing set, and the performance of the model is evaluated through cross validation. And evaluating the classification effect of the model by using indexes such as accuracy, recall, F1 score and the like, and selecting an optimal model for actual classification.
Based on the results of the abnormal state classification, common processing methods and maintenance periods for various abnormal states in the historical maintenance records are analyzed. For "corrosion-like" anomalies, periodic cleaning and recoating of the corrosion protection layer may be found to be an effective maintenance measure, with best performance occurring every two years.
And integrating the maintenance inertia strategies of various abnormal states into a complete storage tank maintenance strategy system, wherein the complete storage tank maintenance strategy system comprises a schedule, maintenance contents, required resources and the like for preventive maintenance.
And the operation data of the storage tank, including pressure, temperature, liquid level, leakage detection and the like, are collected in real time through the sensors of the Internet of things and the monitoring system.
And analyzing the current state of the storage tank by utilizing real-time data, and predicting the potential abnormal state by combining a machine learning model. And dynamically adjusting the maintenance strategy of the current storage tank according to the real-time analysis result and the historical maintenance strategy so as to more accurately cope with the actual situation.
And distributing maintenance tasks to corresponding maintenance teams according to the iterated maintenance strategies. The maintenance team executes maintenance operation according to the task requirement and records detailed information in the maintenance process. After maintenance is completed, state update data of the storage tank is collected, including maintenance effects, residual life assessment and the like, and maintenance records of the storage tank are updated.
And (3) carrying out health assessment on the storage tank by using the state update data, and quantifying the health condition of the storage tank by adopting a scoring mechanism or a grading system. And predicting possible abnormal states in the future according to the health evaluation result of the storage tank, and formulating a corresponding pre-maintenance strategy. Policies should include the point in time of preventive maintenance, maintenance content, required resources, etc.
And finally, based on the pre-maintenance strategy, a detailed pre-maintenance plan is formulated, and the key nodes are set for state change evaluation. Status data of the storage tank is collected periodically during execution of the pre-maintenance schedule, and maintenance effectiveness is assessed and potential risks are monitored. And determining an event change threshold of the pre-maintenance plan according to the result of the state change evaluation. When the tank status reaches or exceeds the threshold, corresponding modification measures, such as adjusting maintenance plans, increasing maintenance resources, etc., are triggered.
The above is a method embodiment of the present application. Based on the same inventive concept, the embodiment of the application also provides self-adaptive formulating equipment of the storage tank maintenance strategy, and the structure of the self-adaptive formulating equipment is shown in fig. 2.
Fig. 2 is a schematic diagram of an internal structure of an adaptive formulation device for a storage tank maintenance policy according to an embodiment of the present application. As shown in fig. 2, the apparatus includes:
At least one processor 201;
And a memory 202 communicatively coupled to the at least one processor;
Wherein the memory 202 stores instructions executable by the at least one processor, the instructions being executable by the at least one processor 201 to enable the at least one processor 201 to:
Acquiring the operation parameters of the storage tank, and evaluating the health influence degree of the storage tank by the operation parameters of the storage tank to obtain a health influence sequence of the storage tank; based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation; determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence; determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the influence parameters of the health short plates of the storage tank and the current health state of the storage tank; based on preset historical maintenance data, determining a historical maintenance strategy through storage tank maintenance inertia processing, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy.
Some embodiments of the application provide a non-volatile computer storage medium corresponding to the adaptive formulation of a tank maintenance policy of fig. 1, storing computer-executable instructions configured to:
Acquiring the operation parameters of the storage tank, and evaluating the health influence degree of the storage tank by the operation parameters of the storage tank to obtain a health influence sequence of the storage tank; based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation; determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence; determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the influence parameters of the health short plates of the storage tank and the current health state of the storage tank; based on preset historical maintenance data, determining a historical maintenance strategy through storage tank maintenance inertia processing, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy.
The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for the internet of things device and the medium embodiment, since they are substantially similar to the method embodiment, the description is relatively simple, and the relevant points are referred to in the description of the method embodiment.
The system, the medium and the method provided by the embodiment of the application are in one-to-one correspondence, so that the system and the medium also have similar beneficial technical effects to the corresponding method, and the beneficial technical effects of the method are explained in detail above, so that the beneficial technical effects of the system and the medium are not repeated here.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (9)
1. A method for adaptively formulating a maintenance strategy for a storage tank, the method comprising:
Acquiring storage tank operation parameters, and evaluating the storage tank health influence degree of the storage tank operation parameters to obtain a storage tank health influence sequence;
Based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation;
Determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence;
determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the storage tank health short-board influence parameters and the current health state of the storage tank;
Based on preset historical maintenance data, determining a historical maintenance strategy through storage tank maintenance inertia processing, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy; the single parameter accumulation is to perform abnormal accumulation on an influence factor of the storage tank so as to simulate the aging or abrasion of a corresponding part of the storage tank, and the storage tank is characterized in that the storage tank is about to be abnormal under the condition that the part reaches a critical condition;
Carrying out storage tank health influence degree evaluation on the storage tank operation parameters to obtain a storage tank health influence sequence, wherein the method specifically comprises the following steps of:
Performing storage tank operation parameter pretreatment on the storage tank operation parameters to obtain impurity-removed storage tank operation parameter data; wherein, the operation parameter data of the impurity removal storage tank comprises: valve tightness, storage tank pressure, structural variables, storage tank temperature, and seam tightness;
Carrying out storage tank abnormal obvious degree discrimination on the impurity-removed storage tank operation parameter data to determine a storage tank operation parameter obvious degree sequence;
performing abnormal state simulation on the storage tank operation parameters with the obviously lower than a preset threshold in the storage tank operation parameter obviously sequence to determine a first storage tank health influence sequence; wherein the tank abnormal state simulation includes: quantitatively simulating the time of the abnormal state of the storage tank and quantitatively simulating the abnormal degree of the abnormal state of the storage tank;
Performing conventional abnormal influence sequencing on the storage tank operation parameters with the obviously higher than a preset threshold value in the storage tank operation parameter obviously sequence to determine a second storage tank health influence sequence; the abnormal degree of the storage tank is divided into a high degree of clarity which is higher than the threshold value, and represents a part which is not easy to be ignored in the actual working environment of the storage tank, and a low degree of clarity which is lower than the threshold value, and represents a part which is easy to be ignored in the actual working environment of the storage tank;
determining the tank health impact sequence based on the first and second tank health impact sequences.
2. The method for adaptively formulating the maintenance strategy of the storage tank according to claim 1, wherein the determining the storage tank health short-board influencing parameter by accumulating the storage tank operation list parameter based on the storage tank health influencing sequence specifically comprises:
Carrying out storage tank influence factor quantity statistics on the storage tank health influence sequence, and determining the upper limit of the storage tank influence factor corresponding to the storage tank health influence sequence according to the storage tank influence factor quantity obtained by the storage tank influence factor quantity statistics;
based on the upper limit of the storage tank influence factors, obtaining a storage tank abnormal upper limit accumulation sequence by carrying out abnormal upper limit accumulation on each storage tank influence factor;
and determining the influence parameters of the short health plates of the storage tank according to the accumulation sequence of the abnormal upper limit of the storage tank.
3. The method for adaptively formulating a tank maintenance strategy according to claim 1, wherein determining the current state of health of the tank through a tank health assessment based on the tank health impact sequence, comprises:
Acquiring historical operation data of a storage tank, and determining current operation data of the storage tank according to the historical operation data of the storage tank; wherein the tank current operation data comprises: tank run time, tank storage class, tank component replacement data;
determining a matching sequence of current operation data of the storage tank through storage demand analysis of the storage tank based on the storage category of the storage tank and the storage tank health influence sequence;
matching the tank run time with the matching sequence to determine a first tank health coefficient;
Determining current data of the storage tank component according to the storage tank component replacement data;
Matching the current data of the storage tank component with the matching sequence, and carrying out weighted average on the matching result to obtain a second storage tank health coefficient;
determining a current state of health of the tank based on the first tank health coefficient and the second tank health coefficient.
4. The method for adaptively formulating the storage tank maintenance strategy according to claim 1, wherein the determining the storage tank real-time maintenance strategy based on the storage tank health short-board influence parameter and the current health state of the storage tank through analysis of the storage tank historical operation parameter specifically comprises:
Setting the influence parameters of the storage tank health short plates as storage tank health variable data, and performing curve fitting according to the current health state of the storage tank by using the storage tank health variable data to obtain a real-time storage tank maintenance scheme;
determining a real-time upgrading scheme of the storage tank through storage tank upgrading analysis based on the current health state of the storage tank;
and determining the real-time maintenance strategy of the storage tank according to the real-time maintenance scheme of the storage tank and the real-time upgrading scheme of the storage tank.
5. The method for adaptively formulating a maintenance strategy for a storage tank according to claim 1, wherein the determining the maintenance strategy for the storage tank by the storage tank maintenance inertia process based on the preset maintenance data for the storage tank comprises:
Classifying the historical maintenance data into abnormal states of the storage tank, and determining a storage tank maintenance inertia strategy through processing inertia matching of the abnormal states of the storage tank based on classification results of the abnormal states of the storage tank;
and integrating data of the storage tank maintenance inertia strategy to determine the historical maintenance strategy.
6. The method of claim 1, wherein after iterating the real-time storage tank maintenance strategy to a preset historical maintenance strategy to obtain a current storage tank maintenance strategy, the method further comprises:
Based on the current storage tank maintenance strategy, the storage tank is maintained to obtain storage tank state update data;
Performing the tank health assessment on the tank status update data to determine tank current update status data;
And determining a storage tank pre-maintenance strategy according to the current update state data of the storage tank.
7. The method of claim 6, wherein after determining a tank pre-maintenance strategy based on the current updated tank status data, the method further comprises:
Based on the storage tank pre-maintenance strategy, a storage tank pre-maintenance plan is formulated;
and carrying out storage tank pre-maintenance state change evaluation on the storage tank pre-maintenance plan, and determining an event change threshold of the storage tank pre-maintenance plan according to an evaluation result of the storage tank pre-maintenance state change evaluation.
8. An apparatus for adaptively formulating a tank maintenance strategy, the apparatus comprising:
At least one processor;
and a memory communicatively coupled to the at least one processor;
Wherein the memory stores instructions executable by the at least one processor, the instructions are executable by the at least one processor to enable the at least one processor to:
Acquiring storage tank operation parameters, and evaluating the storage tank health influence degree of the storage tank operation parameters to obtain a storage tank health influence sequence;
Based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation;
Determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence;
determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the storage tank health short-board influence parameters and the current health state of the storage tank;
Based on preset historical maintenance data, determining a historical maintenance strategy through storage tank maintenance inertia processing, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy; the single parameter accumulation is to perform abnormal accumulation on an influence factor of the storage tank so as to simulate the aging or abrasion of a corresponding part of the storage tank, and the storage tank is characterized in that the storage tank is about to be abnormal under the condition that the part reaches a critical condition;
Carrying out storage tank health influence degree evaluation on the storage tank operation parameters to obtain a storage tank health influence sequence, wherein the method specifically comprises the following steps of:
Performing storage tank operation parameter pretreatment on the storage tank operation parameters to obtain impurity-removed storage tank operation parameter data; wherein, the operation parameter data of the impurity removal storage tank comprises: valve tightness, storage tank pressure, structural variables, storage tank temperature, and seam tightness;
Carrying out storage tank abnormal obvious degree discrimination on the impurity-removed storage tank operation parameter data to determine a storage tank operation parameter obvious degree sequence;
performing abnormal state simulation on the storage tank operation parameters with the obviously lower than a preset threshold in the storage tank operation parameter obviously sequence to determine a first storage tank health influence sequence; wherein the tank abnormal state simulation includes: quantitatively simulating the time of the abnormal state of the storage tank and quantitatively simulating the abnormal degree of the abnormal state of the storage tank;
Performing conventional abnormal influence sequencing on the storage tank operation parameters with the obviously higher than a preset threshold value in the storage tank operation parameter obviously sequence to determine a second storage tank health influence sequence; the abnormal degree of the storage tank is divided into a high degree of clarity which is higher than the threshold value, and represents a part which is not easy to be ignored in the actual working environment of the storage tank, and a low degree of clarity which is lower than the threshold value, and represents a part which is easy to be ignored in the actual working environment of the storage tank;
determining the tank health impact sequence based on the first and second tank health impact sequences.
9. A non-volatile computer storage medium storing computer-executable instructions for adaptively formulating a tank maintenance policy, the computer-executable instructions configured to:
Acquiring storage tank operation parameters, and evaluating the storage tank health influence degree of the storage tank operation parameters to obtain a storage tank health influence sequence;
Based on the storage tank health influence sequence, determining storage tank health short-board influence parameters through storage tank operation single parameter accumulation;
Determining the current health state of the storage tank through storage tank health assessment according to the storage tank health influence sequence;
determining a real-time maintenance strategy of the storage tank through analysis of historical operation parameters of the storage tank based on the storage tank health short-board influence parameters and the current health state of the storage tank;
Based on preset historical maintenance data, determining a historical maintenance strategy through storage tank maintenance inertia processing, and iterating the storage tank real-time maintenance strategy to the historical maintenance strategy to obtain a current storage tank maintenance strategy; the single parameter accumulation is to perform abnormal accumulation on an influence factor of the storage tank so as to simulate the aging or abrasion of a corresponding part of the storage tank, and the storage tank is characterized in that the storage tank is about to be abnormal under the condition that the part reaches a critical condition;
Carrying out storage tank health influence degree evaluation on the storage tank operation parameters to obtain a storage tank health influence sequence, wherein the method specifically comprises the following steps of:
Performing storage tank operation parameter pretreatment on the storage tank operation parameters to obtain impurity-removed storage tank operation parameter data; wherein, the operation parameter data of the impurity removal storage tank comprises: valve tightness, storage tank pressure, structural variables, storage tank temperature, and seam tightness;
Carrying out storage tank abnormal obvious degree discrimination on the impurity-removed storage tank operation parameter data to determine a storage tank operation parameter obvious degree sequence;
performing abnormal state simulation on the storage tank operation parameters with the obviously lower than a preset threshold in the storage tank operation parameter obviously sequence to determine a first storage tank health influence sequence; wherein the tank abnormal state simulation includes: quantitatively simulating the time of the abnormal state of the storage tank and quantitatively simulating the abnormal degree of the abnormal state of the storage tank; performing conventional abnormal influence sequencing on the storage tank operation parameters with the obviously higher than a preset threshold value in the storage tank operation parameter obviously sequence to determine a second storage tank health influence sequence; the abnormal degree of the storage tank is divided into a high degree of clarity which is higher than the threshold value, and represents a part which is not easy to be ignored in the actual working environment of the storage tank, and a low degree of clarity which is lower than the threshold value, and represents a part which is easy to be ignored in the actual working environment of the storage tank;
determining the tank health impact sequence based on the first and second tank health impact sequences.
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| US4525782A (en) * | 1981-03-19 | 1985-06-25 | Daimler-Benz Aktiengesellschaft | Process for determining maintenance and serving intervals on motor vehicles |
| CN117808321A (en) * | 2024-01-04 | 2024-04-02 | 杭州市电力设计院有限公司余杭分公司 | Method, device, equipment and medium for evaluating health state of power distribution network |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4525782A (en) * | 1981-03-19 | 1985-06-25 | Daimler-Benz Aktiengesellschaft | Process for determining maintenance and serving intervals on motor vehicles |
| CN117808321A (en) * | 2024-01-04 | 2024-04-02 | 杭州市电力设计院有限公司余杭分公司 | Method, device, equipment and medium for evaluating health state of power distribution network |
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