Intelligent evaluation and diagnosis system for electrical equipment in digital power plants based on multi-source heterogeneous data

Abstract

The present invention discloses an intelligent evaluation and diagnosis system for digital power plant electrical equipment based on multi-source heterogeneous data, which belongs to the technical field of technical equipment evaluation. It solves the problem in the prior art that only production impact is considered during the operation of electrical equipment, resulting in inefficient and inaccurate evaluation. The currently operating electrical equipment is analyzed to determine whether the current production status of the electrical equipment is normal, thereby improving the accuracy of the electrical equipment evaluation; the deployment and use of the electrical equipment during the operation is analyzed to determine whether the deployment and use of the electrical equipment is normal, thereby improving the accuracy of the electrical equipment evaluation and providing an important basis for equipment status evaluation; the electrical equipment is evaluated through production data and management data analysis, production impact and management impact are taken into account, thereby improving the accuracy of the evaluation.

Description

Technical Field

[0001] The present invention belongs to the technical field of technical equipment evaluation, and in particular is a digital power plant electrical equipment intelligent evaluation and diagnosis system based on multi-source heterogeneous data. Background Art

[0002] Digital power plant is a theory and method to improve the value of power plant by quantifying, analyzing, controlling and making decisions on the entire life cycle of the physical and working objects of the power plant. Therefore, digital power plant is neither a project nor a software or system, but a theory and method. The object of this theory and method is the physical objects and working objects of the power plant, and its method is to study how to quantify, analyze, control and make decisions on them from the perspective of the entire life cycle; electrical equipment is a general term for generators, transformers, power lines, circuit breakers and other equipment in the power system. Electrical equipment consists of two parts: power supply and power consumption equipment.

[0003] In the prior art, electrical equipment cannot be accurately evaluated during operation. Considering only the production impact results in inefficient and inaccurate evaluation, which reduces the operating efficiency of the electrical equipment and makes it impossible to accurately maintain the electrical equipment.

[0004] To this end, we propose an intelligent evaluation and diagnosis system for digital power plant electrical equipment based on multi-source heterogeneous data. Summary of the invention

[0005] In view of the deficiencies in the prior art, the purpose of the present invention is to provide an intelligent evaluation and diagnosis system for digital power plant electrical equipment based on multi-source heterogeneous data, which analyzes the currently operating electrical equipment to determine whether the current production status of the electrical equipment is normal, thereby improving the accuracy of the electrical equipment evaluation; analyzes the deployment and use of electrical equipment during operation to determine whether the deployment and use of the electrical equipment is normal, thereby improving the accuracy of the electrical equipment evaluation and providing an important basis for equipment status evaluation; evaluates electrical equipment through production data and management data analysis, taking production impact and management impact into account, thereby improving the accuracy of the evaluation.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] The digital power plant electrical equipment intelligent evaluation and diagnosis system based on multi-source heterogeneous data includes a server, the server is communicatively connected to a quantitative state evaluation unit and an influencing feature selection unit, and the quantitative state evaluation unit is communicatively connected to a production data analysis unit and a management data analysis unit;

[0008] The server generates a quantitative status assessment signal and sends the quantitative status assessment signal to the quantitative status assessment unit; after receiving the quantitative status assessment signal, the quantitative status assessment unit generates a production data analysis signal and a management data analysis signal and sends the production data analysis signal and the management data analysis signal to the production data analysis unit and the management data analysis unit respectively;

[0009] The currently running electrical equipment is analyzed by the production data analysis unit to determine whether the current production status of the electrical equipment is normal, and the abnormal production time period and the normal production time period are obtained through the production data analysis, and are sent to the quantitative status evaluation unit at the same time; the deployment and use of the electrical equipment during operation is analyzed by the management data analysis unit to determine whether the deployment and use of the electrical equipment is normal, and the abnormal management time period and the normal management time period are obtained through the management data analysis, and are sent to the quantitative status evaluation unit at the same time;

[0010] After receiving the production abnormality time period, the production normal time period, the management abnormality time period and the management normal time period, the quantitative state evaluation unit performs a quantitative state evaluation on the current electrical equipment to determine the operating state of the current electrical equipment; generates an evaluation abnormality signal and an evaluation normal signal through the quantitative state evaluation, and sends them together to the server;

[0011] After receiving the assessment abnormality signal, the server generates an impact feature selection signal and sends the impact feature selection signal to the impact feature selection unit. After receiving the impact feature selection signal, the impact feature selection unit selects the impact features of the electrical equipment, obtains the selected production impact features and selected management impact features through impact feature extraction, and manages them.

[0012] Furthermore, the operation process of the production data analysis unit is as follows:

[0013] The electrical equipment is labeled i, where i is a natural number greater than 1, and the partial discharge amount on the surface of the equipment and the power loss amount during the operation of the electrical equipment are collected, and the partial discharge amount on the surface of the equipment and the power loss amount during the operation of the electrical equipment are marked as FDi and SHi respectively; the floating frequency of the voltage value during the operation of the electrical equipment is collected, and the floating frequency of the voltage value during the operation of the electrical equipment is marked as PLi;

[0014] By formula Obtain the production data analysis coefficient Xi of the electrical equipment, where a1, a2 and a3 are all preset proportional coefficients, and a1>a2>a3>0;

[0015] Compare the production data analysis coefficient Xi of the electrical equipment with the production data analysis coefficient threshold:

[0016] If the production data analysis coefficient Xi of the electrical equipment exceeds the production data analysis coefficient threshold, the production data analysis of the corresponding electrical equipment is determined to be abnormal, a production abnormality signal is generated, and the current operation time period is marked as a production abnormality time period, and the production abnormality signal and the production abnormality time period are sent together to the quantitative status evaluation unit;

[0017] If the production data analysis coefficient Xi of the electrical equipment does not exceed the production data analysis coefficient threshold, the production data analysis of the corresponding electrical equipment is judged to be normal, and a normal production signal is generated. At the same time, the current operating time period is marked as a normal production time period, and the normal production signal and the normal production time period are sent together to the quantitative status evaluation unit.

[0018] Furthermore, the operation process of the management data analysis unit is as follows:

[0019] The duration of continuous operation of the electrical equipment during its current operation and the duration of equipment shutdown for rest before the current operation moment of the electrical equipment are collected, and the duration of continuous operation of the electrical equipment during its current operation and the duration of equipment shutdown for rest before the current operation moment of the electrical equipment are compared with the continuous operation duration threshold and the shutdown and rest duration threshold respectively.

[0020] Furthermore, the comparison process of the continuous operation time of the electrical equipment during the current operation and the equipment downtime before the current operation of the electrical equipment with the continuous operation time threshold and the downtime threshold is as follows:

[0021] If the duration of continuous operation of the electrical equipment during the current operation exceeds the continuous operation duration threshold, or the duration of equipment shutdown and repair before the current operation time of the electrical equipment does not exceed the shutdown and repair duration threshold, the corresponding electrical equipment management data analysis is determined to be abnormal, a management abnormality signal is generated, and the current operation time period is marked as a management abnormality time period; and the management abnormality signal and the management abnormality time period are sent together to the quantitative status evaluation unit;

[0022] If the continuous operation time of the electrical equipment during the current operation does not exceed the continuous operation time threshold, and the equipment shutdown and rest time before the current operation time of the electrical equipment exceeds the shutdown and rest time threshold, then the corresponding electrical equipment management data analysis is judged to be normal, and a normal management signal is generated, and the current operation time period is marked as a normal management time period; and the normal management signal and the normal management time period are sent together to the quantitative status evaluation unit.

[0023] Furthermore, the operation process of the quantitative status assessment unit is as follows:

[0024] The production and management abnormal time periods are uniformly marked as problem time periods, and the production and management normal time periods are uniformly marked as qualified time periods;

[0025] The number of problem time periods and qualified time periods within the current electrical equipment operation time period are collected and analyzed.

[0026] Furthermore, the analysis process of the number of problematic time periods and the number of qualified time periods within the current electrical equipment operation time period is as follows:

[0027] If the number of problem time periods within the current electrical equipment operation time period exceeds the number of qualified time periods, or the number of problem time periods exceeds the corresponding number threshold, the current electrical equipment status evaluation is judged to be unqualified, an evaluation abnormality signal is generated and the evaluation abnormality signal is sent to the server; if the number of problem time periods within the current electrical equipment operation time period does not exceed the number of qualified time periods, and the number of problem time periods does not exceed the corresponding number threshold, the current electrical equipment status evaluation is judged to be qualified, an evaluation normal signal is generated and the evaluation normal signal is sent to the server.

[0028] Furthermore, the operation process of the feature selection unit is as follows:

[0029] The electrical equipment corresponding to the evaluation abnormal signal is marked as a feature extraction object, and the operation time period of the feature extraction object is analyzed. If the operation time period of the feature extraction object is a production abnormality time period, the production data is used as the feature extraction target, and the production data of the current production abnormality time period is compared with the production data of the same type of electrical equipment in the corresponding normal production time period;

[0030] If the operating time period of the feature extraction object is a management abnormality time period, the management data is used as the feature extraction target, and the management data of the current management abnormality time period is compared with the management data of the corresponding management normal time period of the same type of electrical equipment.

[0031] Furthermore, the comparison process of the production data of the current abnormal production time period with the production data of the same type of electrical equipment in the corresponding normal production time period is as follows:

[0032] If the corresponding parameters of the sub-data in the production data are inconsistent, the corresponding sub-data is marked as a preset production influencing feature; the frequency of the preset production influencing feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object is collected; if the frequency of the preset production influencing feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object exceeds the corresponding frequency threshold, the corresponding preset production influencing feature is determined to be marked as a selected production influencing feature; if the frequency of the preset production influencing feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object does not exceed the corresponding frequency threshold, the corresponding preset production influencing feature is determined to be marked as an occasional production influencing feature;

[0033] If the corresponding parameters of the sub-data in the production data are consistent, the corresponding sub-data will be marked as irrelevant influencing features; the server will select production influencing features for management and control during the operation of the electrical equipment, and will monitor occasional production influencing features during the operation of the electrical equipment.

[0034] Furthermore, the comparison process of the management data of the current abnormal management time period with the management data of the same type of electrical equipment in the corresponding normal management time period is as follows:

[0035] If the corresponding parameters of the sub-data in the management data are inconsistent, the corresponding sub-data is marked as a preset management impact feature; the frequency of the preset management impact feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object is collected; if the frequency of the preset management impact feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object exceeds the corresponding frequency threshold, the corresponding preset management impact feature is determined to be marked as a selected management impact feature; if the frequency of the preset management impact feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object does not exceed the corresponding frequency threshold, the corresponding preset management impact feature is determined to be marked as a low-probability management impact feature;

[0036] If the corresponding parameters of the sub-data in the management data are consistent, the corresponding sub-data will be marked as irrelevant impact features; the server will select management impact features for control during the operation of the electrical equipment, and low-probability management impact features for monitoring during the operation of the electrical equipment.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] In the present invention, currently running electrical equipment is analyzed to determine whether the current production status of the electrical equipment is normal, thereby improving the accuracy of electrical equipment evaluation; the deployment and use of electrical equipment during operation is analyzed to determine whether the deployment and use of the electrical equipment is normal, thereby improving the accuracy of electrical equipment evaluation and providing an important basis for equipment status evaluation; electrical equipment is evaluated through production data and management data analysis, and production impacts and management impacts are taken into account, thereby improving the accuracy of evaluation; at the same time, the impact features of the electrical equipment are selected, and the accuracy of electrical equipment maintenance can be improved by extracting the impact features of the electrical equipment, and the targeted maintenance can be enhanced to improve the work efficiency of maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0040] Figure 1 It is the overall system block diagram of the present invention. DETAILED DESCRIPTION

[0041] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1 As shown, a digital power plant electrical equipment intelligent evaluation and diagnosis system based on multi-source heterogeneous data includes a server, the server is communicatively connected to a quantitative state evaluation unit and an influencing feature selection unit, and the quantitative state evaluation unit is communicatively connected to a production data analysis unit and a management data analysis unit;

[0043] In the present application, the electrical equipment is represented as a transformer. When the electrical equipment in the power plant is running, the server generates a quantitative state assessment signal and sends the quantitative state assessment signal to the quantitative state assessment unit. After receiving the quantitative state assessment signal, the quantitative state assessment unit generates a production data analysis signal and a management data analysis signal and sends the production data analysis signal and the management data analysis signal to the production data analysis unit and the management data analysis unit respectively.

[0044] After receiving the production data analysis signal, the production data analysis unit analyzes the currently running electrical equipment to determine whether the current production status of the electrical equipment is normal, thereby improving the accuracy of electrical equipment evaluation;

[0045] The electrical equipment is labeled i, where i is a natural number greater than 1, and the partial discharge amount on the surface of the equipment and the power loss amount during the operation of the electrical equipment are collected, and the partial discharge amount on the surface of the equipment and the power loss amount during the operation of the electrical equipment are marked as FDi and SHi respectively; the floating frequency of the voltage value during the operation of the electrical equipment is collected, and the floating frequency of the voltage value during the operation of the electrical equipment is marked as PLi;

[0046] By formula Obtain the production data analysis coefficient Xi of the electrical equipment, where a1, a2 and a3 are all preset proportional coefficients, and a1>a2>a3>0;

[0047] Compare the production data analysis coefficient Xi of the electrical equipment with the production data analysis coefficient threshold:

[0048] If the production data analysis coefficient Xi of the electrical equipment exceeds the production data analysis coefficient threshold, the production data analysis of the corresponding electrical equipment is determined to be abnormal, a production abnormality signal is generated, and the current operating time period is marked as the production abnormality time period, and the production abnormality signal and the production abnormality time period are sent together to the quantitative status evaluation unit; if the production data analysis coefficient Xi of the electrical equipment does not exceed the production data analysis coefficient threshold, the production data analysis of the corresponding electrical equipment is determined to be normal, a production normal signal is generated, and the current operating time period is marked as the production normal time period, and the production normal signal and the production normal time period are sent together to the quantitative status evaluation unit;

[0049] After receiving the management data analysis signal, the management data analysis unit analyzes the deployment and use of the electrical equipment during operation, thereby determining whether the deployment and use of the electrical equipment is normal, thereby improving the accuracy of the electrical equipment evaluation and providing an important basis for the equipment status evaluation;

[0050] The continuous operation time of the electrical equipment during the current operation and the equipment downtime before the current operation time are collected, and the continuous operation time of the electrical equipment during the current operation and the equipment downtime before the current operation time are compared with the continuous operation time threshold and the downtime time threshold respectively:

[0051] If the duration of continuous operation of the electrical equipment during the current operation process exceeds the continuous operation duration threshold, or the duration of equipment shutdown and rest before the current operation time of the electrical equipment does not exceed the shutdown and rest duration threshold, the corresponding electrical equipment management data analysis is determined to be abnormal, and a management abnormality signal is generated, and the current operation time period is marked as a management abnormality time period; and the management abnormality signal and the management abnormality time period are sent together to the quantitative status evaluation unit; if the duration of continuous operation of the electrical equipment during the current operation process does not exceed the continuous operation duration threshold, and the duration of equipment shutdown and rest before the current operation time of the electrical equipment exceeds the shutdown and rest duration threshold, the corresponding electrical equipment management data analysis is determined to be normal, and a management normal signal is generated, and the current operation time period is marked as a management normal time period; and the management normal signal and the management normal time period are sent together to the quantitative status evaluation unit;

[0052] After receiving the production abnormality time period, the normal production time period, the management abnormality time period and the normal management time period, the quantitative status evaluation unit performs a quantitative status evaluation on the current electrical equipment to determine the operating status of the current electrical equipment; the production abnormality time period and the management abnormality time period are uniformly marked as problem time periods, and the normal production time period and the management normal time period are uniformly marked as qualified time periods; the number of problem time periods and the number of qualified time periods in the current electrical equipment operating time period are collected and analyzed: if the number of problem time periods in the current electrical equipment operating time period exceeds the number of qualified time periods, or the number of problem time periods exceeds the corresponding number threshold, it is determined that the current electrical equipment status evaluation is unqualified, an evaluation abnormality signal is generated and the evaluation abnormality signal is sent to the server; if the number of problem time periods in the current electrical equipment operating time period does not exceed the number of qualified time periods, and the number of problem time periods does not exceed the corresponding number threshold, it is determined that the current electrical equipment status evaluation is qualified, an evaluation normal signal is generated and the evaluation normal signal is sent to the server;

[0053] After receiving the evaluation abnormality signal, the server generates an impact feature selection signal and sends the impact feature selection signal to the impact feature selection unit. After receiving the impact feature selection signal, the impact feature selection unit selects the impact feature of the electrical equipment. The impact feature extraction of the electrical equipment can improve the accuracy of the maintenance of the electrical equipment, and can enhance the pertinence of the maintenance, thereby improving the work efficiency of the maintenance.

[0054] The electrical equipment corresponding to the evaluation abnormal signal is marked as a feature extraction object, and the operating time period of the corresponding feature extraction object is analyzed. If the operating time period of the feature extraction object is the production abnormality time period, the production data is used as the feature extraction target, and the production data of the current production abnormality time period is compared with the production data of the same type of electrical equipment in the corresponding normal production time period. If the corresponding parameters of the sub-data in the production data are inconsistent, the corresponding sub-data is marked as a preset production impact feature; the frequency of the preset production impact feature floating affecting the operation of the electrical equipment during the operating time period of the feature extraction object is collected. If the frequency of the preset production impact feature floating affecting the operation of the electrical equipment during the operating time period of the feature extraction object exceeds the corresponding frequency threshold, then Determine that the corresponding preset production impact feature is marked as a selected production impact feature; if the frequency of the preset production impact feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object does not exceed the corresponding frequency threshold, then determine that the corresponding preset production impact feature is marked as an occasional production impact feature; the production data is represented by the relevant parameters and index values ​​of the operation of the electrical equipment, and its corresponding parameters or index values ​​are the sub-data of the corresponding production data, such as voltage, current, temperature, etc. during the operation process; if the corresponding parameters of the sub-data in the production data are consistent, the corresponding sub-data is marked as an irrelevant impact feature; the server will control the selected production impact feature during the operation of the electrical equipment, and monitor the occasional production impact feature during the operation of the electrical equipment;

[0055] If the operation time period of the feature extraction object is the management abnormality time period, the management data is used as the feature extraction target, and the management data of the current management abnormality time period is compared with the management data of the corresponding management normal time period of the same type of electrical equipment. If the corresponding parameters of the sub-data in the management data are inconsistent, the corresponding sub-data is marked as a preset management impact feature; the frequency of the preset management impact feature floating affecting the operation of the electrical equipment in the operation time period of the feature extraction object is collected. If the frequency of the preset management impact feature floating affecting the operation of the electrical equipment in the operation time period of the feature extraction object exceeds the corresponding frequency threshold, the corresponding preset management impact feature is determined to be marked as a selected management impact feature; if the frequency of the preset management impact feature floating affecting the operation of the electrical equipment in the operation time period of the feature extraction object does not exceed the corresponding frequency threshold, the corresponding preset management impact feature is determined to be marked as a low-probability management impact feature; the management data is represented by the parameters of the manual operation of the electrical equipment, such as the equipment operation time, operation interval time, etc. during the operation process; its corresponding parameters or index values ​​are the sub-data of the corresponding management data. If the corresponding parameters of the sub-data in the management data are consistent, the corresponding sub-data is marked as an irrelevant impact feature;

[0056] The server will select management impact features for control during the operation of electrical equipment, and will monitor low-probability management impact features during the operation of electrical equipment.

[0057] The intelligent evaluation and diagnosis system for digital power plant electrical equipment based on multi-source heterogeneous data generates a production data analysis signal and a management data analysis signal through a quantitative state evaluation unit when working, and sends the production data analysis signal and the management data analysis signal to the production data analysis unit and the management data analysis unit respectively; analyzes the currently running electrical equipment through the production data analysis unit to determine whether the current production state of the electrical equipment is normal, and obtains the abnormal production time period and the normal production time period through production data analysis, and sends them to the quantitative state evaluation unit at the same time; analyzes the deployment and use of electrical equipment during operation through the management data analysis unit, so as to determine whether the deployment and use of electrical equipment is normal, and obtains the abnormal management time period and the normal management time period through management data analysis, and sends them to the quantitative state evaluation unit at the same time;

[0058] After the quantitative status assessment unit receives the production abnormality time period, the normal production time period, the management abnormality time period and the management normal time period, it performs a quantitative status assessment on the current electrical equipment to determine the operating status of the current electrical equipment; generates an assessment abnormality signal and an assessment normal signal through quantitative status assessment, and sends them together to the server; after receiving the impact feature selection signal through the impact feature selection unit, the impact features of the electrical equipment are selected, and the selected production impact features and the selected management impact features are obtained through impact feature extraction, and they are managed and controlled.

[0059] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. Intelligent evaluation and diagnosis system for digital power plant electrical equipment based on multi-source heterogeneous data, characterized by: The server is connected to a quantitative state evaluation unit and an influencing feature selection unit by communication, and the quantitative state evaluation unit is connected to a production data analysis unit and a management data analysis unit by communication; The server generates a quantitative status assessment signal and sends the quantitative status assessment signal to the quantitative status assessment unit; after receiving the quantitative status assessment signal, the quantitative status assessment unit generates a production data analysis signal and a management data analysis signal and sends the production data analysis signal and the management data analysis signal to the production data analysis unit and the management data analysis unit respectively; The currently running electrical equipment is analyzed by the production data analysis unit to determine whether the current production status of the electrical equipment is normal, and the abnormal production time period and the normal production time period are obtained through the production data analysis, and are sent to the quantitative status evaluation unit at the same time; the deployment and use of the electrical equipment during operation is analyzed by the management data analysis unit to determine whether the deployment and use of the electrical equipment is normal, and the abnormal management time period and the normal management time period are obtained through the management data analysis, and are sent to the quantitative status evaluation unit at the same time; After receiving the production abnormality time period, the production normal time period, the management abnormality time period and the management normal time period, the quantitative state evaluation unit performs a quantitative state evaluation on the current electrical equipment to determine the operating state of the current electrical equipment; generates an evaluation abnormality signal and an evaluation normal signal through the quantitative state evaluation, and sends them together to the server; After receiving the evaluation abnormality signal, the server generates an impact feature selection signal and sends the impact feature selection signal to the impact feature selection unit. After receiving the impact feature selection signal, the impact feature selection unit selects the impact features of the electrical equipment, obtains the selected production impact features and the selected management impact features through impact feature extraction, and manages and controls them; The operation process of the production data analysis unit is as follows: The electrical equipment is labeled i, where i is a natural number greater than 1, and the partial discharge amount on the surface of the equipment and the power loss amount during the operation of the electrical equipment are collected, and the partial discharge amount on the surface of the equipment and the power loss amount during the operation of the electrical equipment are marked as FDi and SHi respectively; the floating frequency of the voltage value during the operation of the electrical equipment is collected, and the floating frequency of the voltage value during the operation of the electrical equipment is marked as PLi; By formula Obtain the production data analysis coefficient Xi of the electrical equipment, where a1, a2 and a3 are all preset proportional coefficients, and a1>a2>a3>0; Compare the production data analysis coefficient Xi of the electrical equipment with the production data analysis coefficient threshold: If the production data analysis coefficient Xi of the electrical equipment exceeds the production data analysis coefficient threshold, the production data analysis of the corresponding electrical equipment is determined to be abnormal, a production abnormality signal is generated, and the current operation time period is marked as a production abnormality time period, and the production abnormality signal and the production abnormality time period are sent together to the quantitative status evaluation unit; If the production data analysis coefficient Xi of the electrical equipment does not exceed the production data analysis coefficient threshold, the production data analysis of the corresponding electrical equipment is determined to be normal, a normal production signal is generated, and the current operation time period is marked as a normal production time period, and the normal production signal and the normal production time period are sent together to the quantitative status evaluation unit; The operation process of the management data analysis unit is as follows: The continuous operation time of the electrical equipment during the current operation and the equipment downtime before the current operation time are collected, and the continuous operation time of the electrical equipment during the current operation and the equipment downtime before the current operation time are compared with the continuous operation time threshold and the downtime threshold respectively; The specific comparison process of the continuous operation time of the electrical equipment during the current operation and the equipment downtime before the current operation of the electrical equipment with the continuous operation time threshold and the downtime threshold is as follows: If the duration of continuous operation of the electrical equipment during the current operation exceeds the continuous operation duration threshold, or the duration of equipment shutdown and repair before the current operation time of the electrical equipment does not exceed the shutdown and repair duration threshold, the corresponding electrical equipment management data analysis is determined to be abnormal, a management abnormality signal is generated, and the current operation time period is marked as a management abnormality time period; and the management abnormality signal and the management abnormality time period are sent together to the quantitative status evaluation unit; If the duration of continuous operation of the electrical equipment during the current operation does not exceed the continuous operation duration threshold, and the duration of equipment shutdown and repair before the current operation of the electrical equipment exceeds the shutdown and repair duration threshold, it is determined that the corresponding electrical equipment management data analysis is normal, a normal management signal is generated, and the current operation time period is marked as a normal management time period; and the normal management signal and the normal management time period are sent together to the quantitative status evaluation unit; The operation process of the quantitative status assessment unit is as follows: The production and management abnormal time periods are uniformly marked as problem time periods, and the production and management normal time periods are uniformly marked as qualified time periods; Collect the number of problem time periods and qualified time periods during the current operation period of electrical equipment and analyze them; The specific analysis process of the number of problem time periods and qualified time periods within the current electrical equipment operation time period is as follows: If the number of problem time periods in the current electrical equipment operation time period exceeds the number of qualified time periods, or the number of problem time periods exceeds the corresponding number threshold, the current electrical equipment state evaluation is determined to be unqualified, an evaluation abnormality signal is generated and the evaluation abnormality signal is sent to the server; if the number of problem time periods in the current electrical equipment operation time period does not exceed the number of qualified time periods, and the number of problem time periods does not exceed the corresponding number threshold, the current electrical equipment state evaluation is determined to be qualified, an evaluation normal signal is generated and the evaluation normal signal is sent to the server; The operation process of the feature selection unit is as follows: The electrical equipment corresponding to the evaluation abnormal signal is marked as a feature extraction object, and the operation time period of the feature extraction object is analyzed. If the operation time period of the feature extraction object is a production abnormality time period, the production data is used as the feature extraction target, and the production data of the current production abnormality time period is compared with the production data of the same type of electrical equipment in the corresponding normal production time period; If the operation time period of the feature extraction object is a management abnormality time period, the management data is used as the feature extraction target, and the management data of the current management abnormality time period is compared with the management data of the corresponding management normal time period of the same type of electrical equipment; The specific process of comparing the production data of the current abnormal production period with the production data of the same type of electrical equipment in the corresponding normal production period is as follows: If the corresponding parameters of the sub-data in the production data are inconsistent, the corresponding sub-data is marked as a preset production influencing feature; the frequency of the preset production influencing feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object is collected; if the frequency of the preset production influencing feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object exceeds the corresponding frequency threshold, the corresponding preset production influencing feature is determined to be marked as a selected production influencing feature; if the frequency of the preset production influencing feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object does not exceed the corresponding frequency threshold, the corresponding preset production influencing feature is determined to be marked as an occasional production influencing feature; If the corresponding parameters of the sub-data in the production data are consistent, the corresponding sub-data will be marked as irrelevant impact features; the server will select production impact features for management and control during the operation of the electrical equipment, and will monitor occasional production impact features during the operation of the electrical equipment; The specific process of comparing the management data of the current abnormal management time period with the management data of the corresponding normal management time period of the same type of electrical equipment is as follows: If the corresponding parameters of the sub-data in the management data are inconsistent, the corresponding sub-data is marked as a preset management impact feature; the frequency of the preset management impact feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object is collected; if the frequency of the preset management impact feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object exceeds the corresponding frequency threshold, the corresponding preset management impact feature is determined to be marked as a selected management impact feature; if the frequency of the preset management impact feature floating affecting the operation of the electrical equipment during the operation time period of the feature extraction object does not exceed the corresponding frequency threshold, the corresponding preset management impact feature is determined to be marked as a low-probability management impact feature; If the corresponding parameters of the sub-data in the management data are consistent, the corresponding sub-data will be marked as irrelevant impact features; the server will select management impact features for control during the operation of the electrical equipment, and low-probability management impact features for monitoring during the operation of the electrical equipment.

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