Compressor shutdown analysis and fault diagnosis method and system, medium and product

Abstract

The invention discloses a compressor shutdown analysis and fault diagnosis method and system, a medium and a product, and relates to the technical field of compressors, and the method comprises the steps that first parameter data within a preset first duration before shutdown of a compressor and second parameter data within a preset second duration after shutdown of the compressor are obtained; according to the first parameter data within the preset first duration and the second parameter data within the preset second duration, a compressor performance curve is determined; based on the compressor performance curve, the shutdown state of the compressor is determined; if the shutdown state of the compressor is an abnormal shutdown state, shutdown reason analysis is conducted on the compressor, and a fault diagnosis report is obtained; and according to the shutdown reason in the fault diagnosis report, matching the improvement scheme with the highest relevancy in a preset improvement scheme database. By implementing the method, the comprehensiveness and accuracy of the shutdown diagnosis result of the compressor can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of compressors, and in particular to a compressor shutdown analysis and fault diagnosis method, system, medium and product. Background Art

[0002] In the field of industrial manufacturing and energy, compressors are key mechanical equipment, and their operating status directly affects the efficiency and safety of the entire production line. The compressor may suddenly stop due to various reasons during operation, which may not only lead to production interruptions, but also cause safety accidents. Therefore, real-time monitoring and fault diagnosis of the compressor's operating status, as well as timely handling of shutdown events, are important measures to improve production efficiency and ensure equipment safety.

[0003] In the related art, most compressor control systems monitor the compressor's key parameters such as pressure, temperature, flow, etc., and analyze the compressor's operating conditions through a preset algorithm. When abnormal parameters are detected, the compressor control system automatically issues a warning signal and may trigger the compressor's shutdown procedure to prevent equipment damage.

[0004] Although the relevant technology can monitor and respond to abnormal shutdown of compressors to a certain extent, it has certain limitations in fault diagnosis and processing after shutdown. For example, when the compressor suddenly stops, if only the real-time data before the shutdown is relied upon to judge the fault, the parameters that may continue to change after the shutdown are often ignored, resulting in incomplete or inaccurate diagnosis results. Summary of the invention

[0005] The present application provides a compressor shutdown analysis and fault diagnosis method, system, medium and product for improving the comprehensiveness and accuracy of compressor shutdown diagnosis results.

[0006] In a first aspect, the present application provides a compressor shutdown analysis and fault diagnosis method, which is applied to a control system, and the method includes: obtaining first parameter data within a preset first time length before the compressor shuts down and second parameter data within a preset second time length after the compressor shuts down, the first parameter data being used to represent the operating status of the compressor before shutdown, and the second parameter data packet being used to represent the operating status of the compressor after shutdown; determining a compressor performance curve based on the first parameter data within the preset first time length and the second parameter data within the preset second time length; determining a shutdown state of the compressor based on the compressor performance curve, the shutdown state including a normal shutdown state and an abnormal shutdown state; if the shutdown state of the compressor is the abnormal shutdown state, performing a shutdown cause analysis on the compressor to obtain a fault diagnosis report; and matching the most relevant improvement plan in a preset improvement plan database based on the shutdown cause in the fault diagnosis report.

[0007] By adopting the above technical solution, the control system obtains the parameter data before and after the compressor stops, determines the compressor performance curve, and then determines whether the compressor's stop state is abnormal, thereby realizing accurate identification of the compressor's stop state. For abnormal shutdowns, the control system needs to analyze the cause of the shutdown and generate a fault diagnosis report, which helps to promptly discover and resolve compressor failures. In addition, the control system matches the most relevant improvement plan based on the cause of the shutdown and improves the compressor. This comprehensive analysis and diagnosis process can not only improve the reliability and safety of the compressor's operation, but also extend the service life of the equipment and reduce the economic losses caused by unplanned shutdowns. At the same time, by establishing a preset improvement plan database, this method can continuously accumulate and utilize historical experience to continuously optimize the performance and reliability of the compressor.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the shutdown state of the compressor is determined based on the compressor performance curve, and the shutdown state includes a normal shutdown state and an abnormal shutdown state, specifically including: obtaining a historical performance curve of the compressor when it is shut down multiple times within a historical duration, the historical performance curve is determined according to first parameter data within a preset first duration before the compressor is shut down and second parameter data within a preset second duration after the compressor is shut down, and the historical performance curve corresponds to a normal shutdown state or an abnormal shutdown state; using the historical performance curve as an input feature and the normal shutdown state or the abnormal shutdown state as an output feature, training a preset model to obtain the shutdown state recognition model; inputting the compressor performance curve into the shutdown state recognition model to obtain the shutdown state of the compressor.

[0009] By adopting the above technical solution, the control system determines the shutdown state of the compressor by establishing a shutdown state recognition model, which can make full use of the experience accumulated from the long-term operation of the compressor and improve the accuracy of shutdown state recognition. In addition, the method has good scalability and can update and optimize the shutdown state recognition model by continuously adding new historical data, so that the effect of shutdown state recognition is continuously improved with the increase of usage time, thereby improving the intelligence level and accuracy of compressor shutdown analysis.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the shutdown state of the compressor is determined based on the compressor performance curve, and the shutdown state includes a normal shutdown state and an abnormal shutdown state, specifically including: obtaining a historical performance curve of the compressor when it is shut down multiple times within a historical duration, the historical performance curve is determined according to first parameter data within a preset first duration before the compressor is shut down and second parameter data within a preset second duration after the compressor is shut down, and the historical performance curve corresponds to a normal shutdown state or an abnormal shutdown state; calculating the similarity between the compressor performance curve and the historical performance curve; determining the historical performance curve whose similarity exceeds a preset similarity threshold as a reference curve, and the reference curve corresponds to a normal shutdown state or an abnormal shutdown state; based on the reference curve, determining the shutdown state of the compressor.

[0011] By adopting the above technical solution, the control system compares the compressor performance curve with the historical performance curve to determine the shutdown status, thereby accurately distinguishing between normal shutdown and abnormal shutdown, which helps to detect compressor failures in time, reduce troubleshooting time, and improve the efficiency of compressor maintenance and repair.

[0012] In combination with some embodiments of the first aspect, in some embodiments, if the shutdown state of the compressor is the abnormal shutdown state, the shutdown cause of the compressor is analyzed to obtain a fault diagnosis report, which specifically includes: collecting historical operation data of the compressor; extracting characteristic parameters in the historical operation data to determine the normal operating range of the parameters of the compressor; comparing the first parameter data within a preset first time length before the compressor is shut down and the second parameter data within a preset second time length after the shutdown with the normal operating range of the parameters to determine the abnormal parameters; obtaining the abnormal cause corresponding to the abnormal parameter in an abnormal parameter knowledge base, the abnormal parameter knowledge base including the abnormal parameter range and the corresponding abnormal cause; based on the abnormal cause, generating the fault diagnosis report.

[0013] By adopting the above technical solution, firstly, the control system uses historical operating data to establish the normal operating range of parameters, making abnormal judgment more objective and accurate, avoiding the subjective errors that may be caused by relying solely on experience judgment. Secondly, the control system can quickly locate the cause of the abnormality by establishing an abnormal parameter knowledge base, greatly improving the efficiency of fault diagnosis. Furthermore, this method can detect multiple abnormal parameters, thereby comprehensively analyzing the possible causes of the fault and improving the accuracy and reliability of the diagnosis. In addition, by generating a fault diagnosis report, it provides users with clear fault information and processing guidance, which helps to quickly solve the problem.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of determining the shutdown state of the compressor based on the compressor performance curve, wherein the shutdown state includes a normal shutdown state and an abnormal shutdown state, the method further includes: if the shutdown state of the compressor is the normal shutdown state, predicting the performance trend of the compressor based on the first parameter data within a preset first time length before the compressor is shut down and the second parameter data within a preset second time length after the compressor is shut down; judging whether the performance trend is lower than a preset performance red line; if lower, determining the optimization parameters of the compressor and making corresponding adjustments.

[0015] By adopting the above technical solution, after the control system determines that the compressor is in a normal shutdown state, it further analyzes and predicts the performance trend of the compressor, and makes timely optimization adjustments based on the prediction results. This method realizes the transformation from passive maintenance to active prevention, effectively reduces the risk of major equipment failures, and makes optimization adjustments before the equipment performance has significantly declined, which helps to maintain the optimal operating state of the compressor and extend the life of the equipment. In addition, through continuous performance monitoring and optimization, the energy efficiency of the compressor can be improved, operating costs can be reduced, unnecessary downtime can be avoided, and production efficiency can be improved.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of matching the most relevant improvement plan in a preset improvement plan database according to the shutdown cause in the fault diagnosis report, the method also includes: after the user implements the improvement plan, obtaining the number of shutdowns and the shutdown cause of the compressor; and scoring the improvement plan based on the number of shutdowns and the shutdown cause.

[0017] By adopting the above technical solution, after the user implements the improvement plan, the control system obtains the number of compressor shutdowns and the reasons for shutdowns, and scores the improvement plan, thereby establishing a closed-loop improvement evaluation mechanism that can objectively quantify the actual effect of the improvement plan and avoid the deviation that may be caused by subjective judgment. By continuously tracking and evaluating the improvement plan, inappropriate improvement measures can be discovered and adjusted in a timely manner to ensure continuous optimization of compressor performance.

[0018] In combination with some embodiments of the first aspect, in some embodiments, if the shutdown state of the compressor is the abnormal shutdown state, then the shutdown cause of the compressor is analyzed to obtain a fault diagnosis report, the method also includes: obtaining the operating status of other equipment when the compressor is shut down; analyzing the correlation between the operating status of the other equipment and the shutdown of the compressor; if there is a correlation, adding the operating status of the relevant other equipment to the fault diagnosis report.

[0019] By adopting the above technical solution, the control system obtains the operating status of other equipment when the compressor stops, analyzes its correlation with the compressor shutdown, and adds relevant information to the fault diagnosis report, thereby expanding the scope of analysis from a single device to the entire system, which helps to discover potential system-level problems. By analyzing the correlation between the compressor and other equipment, possible chain reactions or root causes can be identified, thereby improving the comprehensiveness and accuracy of fault diagnosis.

[0020] In a second aspect, an embodiment of the present application provides a control system, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the control system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when the computer program product is run on a control system, enables the control system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a control system, enable the control system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] It is understandable that the control system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By adopting the above technical solution, the control system obtains the parameter data before and after the compressor stops, determines the compressor performance curve, and then determines whether the compressor's stop state is abnormal, thereby realizing accurate identification of the compressor's stop state. For abnormal shutdowns, the control system needs to analyze the cause of the shutdown and generate a fault diagnosis report, which helps to promptly discover and resolve compressor failures. In addition, the control system matches the most relevant improvement plan based on the cause of the shutdown and improves the compressor. This comprehensive analysis and diagnosis process can not only improve the reliability and safety of the compressor's operation, but also extend the service life of the equipment and reduce the economic losses caused by unplanned shutdowns. At the same time, by establishing a preset improvement plan database, this method can continuously accumulate and utilize historical experience to continuously optimize the performance and reliability of the compressor.

[0025] 2. By adopting the above technical solution, after the control system determines that the compressor is in a normal shutdown state, it further analyzes and predicts the performance trend of the compressor, and optimizes and adjusts it in time according to the prediction results. This method realizes the transformation from passive maintenance to active prevention, effectively reduces the risk of major equipment failure, and optimizes and adjusts before the performance of the equipment has obviously declined, which helps to maintain the best operating state of the compressor and extend the life of the equipment. In addition, through continuous performance monitoring and optimization, the energy efficiency of the compressor can be improved, operating costs can be reduced, unnecessary downtime can be avoided, and production efficiency can be improved.

[0026] 3. By adopting the above technical solution, the control system obtains the operating status of other equipment when the compressor stops, analyzes its correlation with the compressor shutdown, and adds relevant information to the fault diagnosis report, thereby expanding the scope of analysis from a single device to the entire system, which helps to discover potential system-level problems. By analyzing the correlation between the compressor and other equipment, possible chain reactions or root causes can be identified, thereby improving the comprehensiveness and accuracy of fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of a compressor shutdown analysis and fault diagnosis method in an embodiment of the present application; Figure 2 is another flow chart of the compressor shutdown analysis and fault diagnosis method in the embodiment of the present application; Figure 3 It is a schematic diagram of the structure of a physical device of the control system in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] The following is a description of the process of the method provided by this implementation. Figure 1 , is a flow chart of the compressor shutdown analysis and fault diagnosis method in an embodiment of the present application.

[0031] S101, obtaining first parameter data within a preset first time period before the compressor is shut down and second parameter data within a preset second time period after the compressor is shut down, wherein the first parameter data is used to indicate the operating status of the compressor before the compressor is shut down, and the second parameter data is used to indicate the operating status of the compressor after the compressor is shut down; Among them, the compressor refers to a mechanical equipment used to compress and transport gas. Shutdown refers to the process of the compressor changing from an operating state to a non-operating state. The preset first duration refers to a period of time set before the compressor shuts down, which may usually range from a few minutes to a few hours. The preset second duration refers to a period of time set after the compressor shuts down, which may range from a few minutes to a few days. The first parameter data refers to the operating parameters of the compressor collected within the preset first duration, such as temperature, pressure, flow, etc. The second parameter data refers to the relevant parameters of the compressor collected within the preset second duration, which may include data such as residual heat and pressure release after shutdown, and may also be operating parameters corresponding to the first parameter data, such as temperature, pressure, flow, etc. The operating status refers to the working status of the compressor. The control system refers to an automated system that monitors and manages the operation of the compressor.

[0032] The control system executes this step when a compressor shutdown event is detected. Specifically, first, the control system determines the shutdown time of the compressor, and then traces back to the preset first time period to collect the first parameter data of the compressor during this period, including but not limited to the compressor's inlet and outlet pressure, temperature, flow, power consumption, vibration data, etc. At the same time, the control system will continue to monitor the second parameter data of the compressor within the preset second time period after the shutdown, which may include pressure data, temperature data, vibration data, etc. after the shutdown. The control system may use high-frequency sampling technology to ensure the accuracy and continuity of the data, especially at critical moments before and after the shutdown.

[0033] S102, determining a compressor performance curve according to the first parameter data within the preset first time length and the second parameter data within the preset second time length; The control system executes this step immediately after completing the data collection of step S101. Specifically, first, the control system preprocesses the collected first parameter data and second parameter data, including data cleaning, outlier processing and data standardization. Then, the control system selects key parameters, such as pressure ratio, flow rate, efficiency, etc., as the vertical axis indicators of the compressor performance curve. With time as the horizontal axis, the curves of the changes of these key parameters over time are plotted to obtain the compressor performance curve. The control system may use an interpolation algorithm to smooth the compressor performance curve and use regression analysis to find the trend of changes in key parameters. At the same time, the control system may also draw combined curves of multiple parameters, such as pressure-flow curves, efficiency-load curves, etc., to fully reflect the performance changes of the compressor. These compressor performance curves will intuitively show the performance changes of the compressor from normal operation to shutdown, and then to the entire process after shutdown, providing an important basis for subsequent state judgment and fault diagnosis.

[0034] S103, determining a shutdown state of the compressor based on the compressor performance curve, where the shutdown state includes a normal shutdown state and an abnormal shutdown state; Among them, the normal shutdown state means that the compressor is shut down as expected or planned, and all parameters are within a reasonable range. The abnormal shutdown state refers to an unplanned shutdown caused by a fault or unexpected situation.

[0035] Optionally, under normal circumstances, based on the compressor performance curve, determining the shutdown state of the compressor can be achieved in the following manner: obtaining a historical performance curve of the compressor when it is shut down multiple times within a historical duration, wherein the historical performance curve corresponds to a normal shutdown state or an abnormal shutdown state based on first parameter data within a preset first duration before the compressor is shut down and second parameter data within a preset second duration after the compressor is shut down; using the historical performance curve as an input feature and the normal shutdown state or the abnormal shutdown state as an output feature, training a preset model to obtain the shutdown state recognition model; inputting the compressor performance curve into the shutdown state recognition model to obtain the shutdown state of the compressor.

[0036] Optionally, under normal circumstances, based on the compressor performance curve, determining the shutdown state of the compressor can be achieved in the following manner: obtaining a historical performance curve of the compressor when it is shut down multiple times within a historical duration, wherein the historical performance curve is determined based on first parameter data within a preset first duration before the compressor is shut down and second parameter data within a preset second duration after the compressor is shut down, and the historical performance curve corresponds to a normal shutdown state or an abnormal shutdown state; calculating the similarity between the compressor performance curve and the historical performance curve; determining the historical performance curve whose similarity exceeds a preset similarity threshold as a reference curve, and the reference curve corresponds to a normal shutdown state or an abnormal shutdown state; based on the reference curve, determining the shutdown state of the compressor.

[0037] S104: If the shutdown state of the compressor is the abnormal shutdown state, analyzing the shutdown cause of the compressor to obtain a fault diagnosis report; Among them, shutdown cause analysis refers to the process of systematically investigating and judging the factors that lead to abnormal shutdown of the compressor. Fault diagnosis report refers to a detailed description of the cause of abnormal shutdown of the compressor and related information.

[0038] The control system executes this step immediately after determining that the compressor is in an abnormal shutdown state. Specifically, first, the control system calls a preset fault diagnosis algorithm, which may be determined based on an expert, machine learning, or deep learning model. The control system uses the previously collected first parameter data and second parameter data, as well as the generated compressor performance curve as input, and feeds them into the fault diagnosis algorithm. The fault diagnosis algorithm analyzes the temporal relationship of parameter abnormalities, identifies key abnormal parameters, and matches them with the fault feature library. At the same time, the control system may consider auxiliary information such as environmental factors and equipment operation history to improve the accuracy of diagnosis. During the diagnosis process, the control system may use methods such as decision trees or Bayesian networks to infer possible causes of the fault. For complex faults, the control system may use a multi-model fusion method to integrate multiple diagnostic results. Finally, the control system generates a detailed fault diagnosis report, which includes the fault type, possible causes, timeline of the fault, scope of impact, fault severity assessment, recommended maintenance measures, and suggestions for preventing similar faults.

[0039] S105 . According to the shutdown cause in the fault diagnosis report, the most relevant improvement solution is matched in a preset improvement solution database.

[0040] The control system performs this step immediately after generating a fault diagnosis report. Specifically, first, the control system extracts the cause of downtime from the fault diagnosis report. Then, the control system accesses the preset improvement solution database, which may be a structured knowledge base containing a large number of historical downtime cases and historical downtime causes and corresponding improvement solutions. The control system uses natural language processing technology or semantic analysis algorithms to match the cause of downtime with the improvement solutions in the preset improvement solution database. The matching process may use techniques such as vector space models or latent semantic analysis to calculate the similarity score between the cause of downtime and each improvement solution. The control system may also consider multiple factors to evaluate the relevance, such as the exact match of the fault type, the similarity of the equipment model, the similarity of the operating environment, etc. Finally, the control system selects one or more improvement solutions with the highest relevance, and may make appropriate adjustments to the improvement solutions based on the current specific situation. The selected improvement solution will include detailed implementation steps, required resources, expected results and other information to provide clear guidance for maintenance personnel.

[0041] By adopting the above technical solution, the control system obtains the parameter data before and after the compressor stops, determines the compressor performance curve, and then determines whether the compressor's stop state is abnormal, thereby realizing accurate identification of the compressor's stop state. For abnormal shutdowns, the control system needs to analyze the cause of the shutdown and generate a fault diagnosis report, which helps to promptly discover and resolve compressor failures. In addition, the control system matches the most relevant improvement plan based on the cause of the shutdown and improves the compressor. This comprehensive analysis and diagnosis process can not only improve the reliability and safety of the compressor's operation, but also extend the service life of the equipment and reduce the economic losses caused by unplanned shutdowns. At the same time, by establishing a preset improvement plan database, this method can continuously accumulate and utilize historical experience to continuously optimize the performance and reliability of the compressor.

[0042] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the compressor shutdown analysis and fault diagnosis method in an embodiment of the present application.

[0043] S201, obtaining first parameter data within a preset first time length before the compressor is shut down and second parameter data within a preset second time length after the compressor is shut down, wherein the first parameter data is used to indicate the operating status of the compressor before the compressor is shut down, and the second parameter data is used to indicate the operating status of the compressor after the compressor is shut down; For details, please refer to step S101, which will not be described in detail here.

[0044] S202, determining a compressor performance curve according to the first parameter data within the preset first time length and the second parameter data within the preset second time length; For details, please refer to step S101, which will not be described in detail here.

[0045] S203, determining a shutdown state of the compressor based on the compressor performance curve, where the shutdown state includes a normal shutdown state and an abnormal shutdown state; For details, please refer to step S101, which will not be described in detail here.

[0046] S204: If the shutdown state of the compressor is the normal shutdown state, predicting the performance trend of the compressor according to the first parameter data within a preset first time length before the compressor is shut down and the second parameter data within a preset second time length after the compressor is shut down; This step is performed after the control system determines that the compressor is in a normal shutdown state, and is used to predict future performance changes of the compressor. Specifically, first, the control system extracts the first parameter data within the first preset time length before shutdown and the second parameter data within the second preset time length after shutdown. Then, the control system inputs these two sets of parameter data into a pre-trained machine learning model or uses statistical analysis methods to calculate the changing trends of a series of performance indicators, namely, performance trends. This performance trend may appear as linear growth, exponential decay, or other patterns, reflecting the changes in compressor performance over time. In this way, the control system can predict the performance changes of the compressor in the future.

[0047] S205, determining whether the performance trend is lower than a preset performance red line; The preset performance redline refers to the preset minimum acceptable level of compressor performance, which is usually recommended by the equipment manufacturer or determined based on actual operating experience. A performance trend below the preset performance redline indicates that the future performance of the compressor will drop to an unacceptable level.

[0048] This step is performed immediately after the performance trend of the compressor is obtained, and is used to evaluate whether the future performance of the compressor meets the operating requirements. Specifically, first, the control system retrieves the preset performance redline, which may include the minimum allowable values ​​of multiple key performance indicators, such as minimum efficiency, maximum allowable energy consumption, etc. Then, the control system compares the performance trend predicted in step S204 with the preset performance redline. The comparison method may include simple numerical comparison or may involve more complex statistical analysis, such as calculating the time point when the performance trend intersects the preset performance redline.

[0049] S206: If it is lower than, determine the optimized parameters of the compressor and make corresponding adjustments; The optimization parameters refer to adjustable parameters that can improve the performance of the compressor, such as intake pressure, cooling water temperature, lubricating oil quality, etc. The corresponding adjustment refers to a specific adjustment operation performed on the compressor according to the determined optimization parameters.

[0050] This step is performed after the control system determines that the performance trend is lower than the preset performance red line. It aims to prevent the performance of the compressor from deteriorating by adjusting the compressor parameters in a timely manner. Specifically, first, the control system analyzes the possible reasons for the decline in performance trend, which may involve in-depth analysis of historical data. Based on the analysis results, the control system determines the optimization parameters that are most likely to improve the performance of the compressor. These optimization parameters may include compression ratio, cooling efficiency, lubrication system settings, etc. Next, the control system will generate a specific adjustment plan based on these optimization parameters. The adjustment may be automatic, such as directly adjusting the relevant settings through the control system; it may also require manual intervention. At this time, the control system will generate detailed adjustment guidance suggestions for the operator to execute. After the adjustment is completed, the control system will continue to monitor the performance of the compressor, evaluate the adjustment effect, and perform further optimization when necessary.

[0051] S207, if the shutdown state of the compressor is the abnormal shutdown state, analyzing the shutdown cause of the compressor to obtain a fault diagnosis report; For details, please refer to step S101, which will not be described in detail here.

[0052] S208, obtaining the operating status of other equipment when the compressor is shut down; Among them, other equipment refers to machinery and equipment associated with the compressor or in the same production system, such as cooling systems, piping systems, power supply equipment, etc. The operating status refers to the working conditions of these other equipment when the compressor is stopped, including but not limited to switch status, operating parameters, alarm information, etc.

[0053] This step is performed immediately when the compressor stops. Specifically, first, the control system identifies all other equipment directly or indirectly related to the compressor, which may include upstream gas supply equipment, downstream gas consumption equipment, auxiliary cooling equipment, etc. Then, the control system obtains the operating status of these other equipment in real time through various sensors, controllers or data interfaces. The operating status may include the switch status of other equipment, operating parameters (such as temperature, pressure, flow, etc.), efficiency indicators, alarm information, etc. The control system preliminarily processes and stores the operating status of these other equipment in preparation for subsequent analysis.

[0054] S209, analyzing the correlation between the operating status of the other equipment and the shutdown of the compressor; Among them, correlation refers to the possible causal relationship or statistical association between the operating status of other equipment and compressor shutdown.

[0055] This step is performed immediately after obtaining the operating status of other equipment, and aims to determine whether the compressor shutdown is related to the abnormality of other equipment. Specifically, first, the control system preprocesses the collected operating status of other equipment, including data cleaning, standardization and other operations. Then, the control system may use a variety of analysis methods to explore the correlation between the operating status of other equipment and the compressor shutdown. This may include time series analysis to see whether the abnormality of other equipment precedes or occurs at the same time as the compressor shutdown; correlation analysis to calculate the statistical correlation coefficient between the key parameters of other equipment and the compressor shutdown; causal inference models, such as Bayesian networks, to infer possible causal relationships. In addition, the control system may also use pre-trained machine learning models, such as decision trees or random forests, to identify which other equipment's operating status has a significant impact on the compressor shutdown. Through these analyses, the control system can quantify the degree of correlation between the operating status of other equipment and the compressor shutdown, providing important clues for subsequent fault diagnosis.

[0056] S210, if there is a correlation, adding the operating status of other related devices to the fault diagnosis report; The existence of correlation means that through the analysis of step S210, it is determined that there is a significant statistical correlation or possible causal relationship between the operating status of certain other equipment and the compressor shutdown.

[0057] This step is performed after the correlation analysis is completed, with the aim of enriching the content of the fault diagnosis report and providing a more comprehensive fault analysis perspective. Specifically, first, the control system sets a correlation threshold, and only correlations that exceed this correlation threshold are considered significant. For other equipment determined to be significantly correlated, the control system extracts their operating status, including abnormal parameters, the time frequency of abnormal occurrence, the duration of abnormal occurrence, etc. The control system then adds this information to the fault diagnosis report in a structured form. This may include creating a new report section, such as "Abnormal Condition of Related Equipment"; or adding a new paragraph to the existing "Fault Analysis" section. The added content includes not only the raw data, but may also include preliminary analysis conclusions generated by the control system, such as "The abnormal temperature increase of cooling tower #2 may have caused the overheating shutdown of the compressor." In this way, the fault diagnosis report can provide a more systematic and comprehensive fault analysis perspective, helping maintenance personnel to locate and solve problems more quickly and accurately.

[0058] S211. After the user implements the improvement plan, the number of shutdowns and the reasons for the shutdowns of the compressor are obtained; Improvement plan refers to the specific measures and operating procedures formulated to solve compressor failures or optimize performance. User implementation refers to the actual adjustments and improvement operations performed by operators or maintenance personnel in accordance with the improvement plan. The number of shutdowns refers to the frequency of compressor shutdowns within a certain period of time. The shutdown reason is used to indicate the specific problem or triggering condition that caused the compressor to shut down, which may include planned shutdown, fault shutdown, safety protection shutdown, etc.

[0059] This step is performed within a period of time after the implementation of the improvement plan, with the purpose of collecting data to evaluate the effectiveness of the improvement plan. Specifically, first, the control system sets an observation period, which may usually be a few weeks to a few months, depending on the operating cycle of the compressor and the expected effect of the improvement plan. During this observation period, the control system continuously monitors the operating status of the compressor and records each shutdown event. For each shutdown, the control system not only records the time and duration of its occurrence, but also determines the cause of the shutdown by analyzing various parameters and alarm information at the time of the shutdown. These reasons may include but are not limited to: normal planned shutdowns, upstream gas supply interruptions, safety shutdowns triggered by overheating protection, emergency shutdowns caused by mechanical failures, etc. The control system classifies and counts this information, calculates the total number of shutdowns during the observation period, and the distribution of various shutdown reasons.

[0060] S212, scoring the improvement plan based on the number of downtimes and the downtime reasons; This step is performed after sufficient downtime data has been collected, and is intended to objectively evaluate the effectiveness of the improvement plan. Specifically, first, the control system needs to establish a scoring standard. This scoring standard may include multiple dimensions: Improvement of downtime frequency: Compare the number of downtimes per unit time before and after the improvement, and calculate the reduction ratio.

[0061] Specific fault improvement: Calculate the degree of reduction in the frequency of related downtime causes for the specific problem targeted by the improvement plan.

[0062] Overall reliability improvement: Assess the reduction in unplanned downtime.

[0063] Performance improvement: If the improvement plan aims to improve efficiency, it is also necessary to consider the improvement of indicators such as energy consumption and output.

[0064] The control system inputs the collected data on the number of downtimes and reasons for downtime into the scoring model. For example, if the improvement plan is mainly aimed at overheating, the control system will pay special attention to whether the number of downtimes caused by overheating has been significantly reduced. The scoring model may use a weighted average method to give different weights to different dimensions and finally obtain a comprehensive score.

[0065] In addition, the control system may also compare this comprehensive score with the scores of other improvement plans in history, or with the preset target score, to give a more relative evaluation. For example, the numerical score may be supplemented with qualitative descriptions such as "significant improvement", "slight improvement", "no obvious effect", "poor effect", etc.

[0066] S213: According to the shutdown cause in the fault diagnosis report, the most relevant improvement solution is matched in a preset improvement solution database.

[0067] For details, please refer to step S105, which will not be described in detail here.

[0068] By adopting the above technical solution, after the control system determines that the compressor is in a normal shutdown state, it further analyzes and predicts the performance trend of the compressor, and makes timely optimization adjustments based on the prediction results. This method realizes the transformation from passive maintenance to active prevention, effectively reduces the risk of major equipment failures, and makes optimization adjustments before the equipment performance has significantly declined, which helps to maintain the optimal operating state of the compressor and extend the life of the equipment. In addition, through continuous performance monitoring and optimization, the energy efficiency of the compressor can be improved, operating costs can be reduced, unnecessary downtime can be avoided, and production efficiency can be improved.

[0069] By adopting the above technical solution, the control system obtains the operating status of other equipment when the compressor stops, analyzes its correlation with the compressor shutdown, and adds relevant information to the fault diagnosis report, thereby expanding the scope of analysis from a single device to the entire system, which helps to discover potential system-level problems. By analyzing the correlation between the compressor and other equipment, possible chain reactions or root causes can be identified, thereby improving the comprehensiveness and accuracy of fault diagnosis.

[0070] The following describes the control system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the structure of a physical device of the control system in an embodiment of the present application.

[0071] It should be noted that Figure 3 The structure of the control system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0072] like Figure 3As shown, the control system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, the ROM 302 and the RAM 303 are connected to each other through the bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0073] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0074] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0075] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0076] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0077] Specifically, the control system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the compressor shutdown analysis and fault diagnosis method provided in the above embodiment is implemented.

[0078] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the control system described in the above embodiment; or may exist independently without being assembled into the control system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the control system, the control system implements the compressor shutdown analysis and fault diagnosis method provided in the above embodiment.

[0079] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0080] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0081] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A compressor shutdown analysis and fault diagnosis method, characterized in that: Applied to a control system, the method comprises: Acquire first parameter data within a preset first time length before the compressor is shut down and second parameter data within a preset second time length after the compressor is shut down, wherein the first parameter data is used to indicate the operating status of the compressor before the compressor is shut down, and the second parameter data packet is used to indicate the operating status of the compressor after the compressor is shut down; Determining a compressor performance curve according to the first parameter data within the preset first time period and the second parameter data within the preset second time period; Based on the compressor performance curve, determining the shutdown state of the compressor, wherein the shutdown state includes a normal shutdown state and an abnormal shutdown state; If the shutdown state of the compressor is the abnormal shutdown state, analyzing the shutdown cause of the compressor to obtain a fault diagnosis report; According to the shutdown cause in the fault diagnosis report, the most relevant improvement plan is matched in the preset improvement plan database.

2. The method according to claim 1, characterized in that: The shutdown state of the compressor is determined based on the compressor performance curve, and the shutdown state includes a normal shutdown state and an abnormal shutdown state, specifically including: Obtaining a historical performance curve when the compressor is shut down multiple times within a historical duration, wherein the historical performance curve is determined according to first parameter data within a preset first duration before the compressor is shut down and second parameter data within a preset second duration after the compressor is shut down, and the historical performance curve corresponds to a normal shutdown state or an abnormal shutdown state; Taking the historical performance curve as an input feature and the normal shutdown state or the abnormal shutdown state as an output feature, training a preset model to obtain the shutdown state recognition model; The compressor performance curve is input into the shutdown state recognition model to obtain the shutdown state of the compressor.

3. The method according to claim 1, characterized in that The shutdown state of the compressor is determined based on the compressor performance curve, and the shutdown state includes a normal shutdown state and an abnormal shutdown state, specifically including: Obtaining a historical performance curve when the compressor is shut down multiple times within a historical duration, wherein the historical performance curve is determined according to first parameter data within a preset first duration before the compressor is shut down and second parameter data within a preset second duration after the compressor is shut down, and the historical performance curve corresponds to a normal shutdown state or an abnormal shutdown state; Calculating the similarity between the compressor performance curve and the historical performance curve; Determine the historical performance curve whose similarity exceeds a preset similarity threshold as a reference curve, wherein the reference curve corresponds to a normal shutdown state or an abnormal shutdown state; Based on the reference curve, a stop state of the compressor is determined.

4. The method according to claim 1, characterized in that If the shutdown state of the compressor is the abnormal shutdown state, the shutdown cause of the compressor is analyzed to obtain a fault diagnosis report, which specifically includes: Collecting historical operating data of the compressor; Extracting characteristic parameters from the historical operation data to determine a normal operating range of parameters of the compressor; Compare the first parameter data within a preset first time period before the compressor is shut down and the second parameter data within a preset second time period after the compressor is shut down with the normal operating range of the parameters to determine the abnormal parameters; In an abnormal parameter knowledge base, obtaining an abnormal cause corresponding to the abnormal parameter, wherein the abnormal parameter knowledge base includes an abnormal parameter range and a corresponding abnormal cause; Based on the abnormal cause, the fault diagnosis report is generated.

5. The method according to claim 1, characterized in that After the step of determining the shutdown state of the compressor based on the compressor performance curve, wherein the shutdown state includes a normal shutdown state and an abnormal shutdown state, the method further includes: If the shutdown state of the compressor is the normal shutdown state, predicting the performance trend of the compressor according to the first parameter data within a preset first time length before the compressor is shut down and the second parameter data within a preset second time length after the compressor is shut down; Determine whether the performance trend is lower than a preset performance red line; If it is lower than that, the optimized parameters of the compressor are determined and adjusted accordingly.

6. The method according to claim 1, characterized in that After the step of matching the most relevant improvement solution in a preset improvement solution database according to the shutdown cause in the fault diagnosis report, the method further includes: After the user implements the improvement plan, the number of shutdowns and the reasons for the shutdowns of the compressor are obtained; The improvement plan is scored based on the number of shutdowns and the reasons for the shutdowns.

7. The method according to claim 1, characterized in that After the step of analyzing the shutdown cause of the compressor and obtaining a fault diagnosis report if the shutdown state of the compressor is the abnormal shutdown state, the method further includes: Obtaining the operating status of other equipment when the compressor is shut down; Analyzing the correlation between the operating status of the other equipment and the shutdown of the compressor; If there is a correlation, the operating status of other related devices is added to the fault diagnosis report.

8. A control system, characterized in that: The control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the control system to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a control system, the control system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a control system, the control system is caused to execute the method according to any one of claims 1 to 7.

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