Electrical equipment maintenance management system and method

Abstract

The invention relates to the technical field of electrical equipment, in particular to an electrical equipment maintenance management system and method. The method applies the system, the system comprises a maintenance planning module which is used for dynamically generating a maintenance period and generating a detailed task allocation scheme in combination with maintenance personnel information, and the process comprises the following steps: setting an initial pheromone concentration, a maximum iteration frequency and an ant number; and defining heuristic information and a target function, sequentially selecting maintenance personnel for each task according to the probability, forming a task allocation scheme corresponding to each ant, calculating a target function value corresponding to each ant, updating pheromones, and outputting an optimal solution. According to the technical scheme, the maintenance cost of the electrical equipment can be reduced, and the maintenance efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical equipment, and in particular to an electrical equipment maintenance management system and method. Background Art

[0002] In the maintenance and management system of large-scale electrical equipment, it is necessary to ensure the continuous and stable operation of the equipment. Due to the dynamic characteristics of electrical equipment maintenance scenarios, such as the irregular occurrence of equipment failures, the differences in the urgency of maintenance tasks, and the constant changes in the status of maintenance personnel (including personnel leave, new employees joining, etc.), maintenance management work has become extremely complicated. Traditional electrical equipment maintenance management systems often use fixed maintenance cycles, which exposes many problems in actual applications.

[0003] First, fixed maintenance cycles are difficult to adapt to the diversity of the actual operating status of equipment. On the one hand, if the maintenance cycle is set too frequently, it will lead to unnecessary waste of resources. For example, some equipment is frequently maintained when it is in good operating condition, which not only consumes a lot of man-hours and spare parts resources, but may also cause unnecessary damage to the equipment due to excessive maintenance. On the other hand, a maintenance cycle that is too long may increase the risk of equipment failure. Once the equipment fails, not only will it require higher maintenance costs, it may also cause a series of problems such as production stagnation and safety hazards, causing significant economic losses and reputation damage to the company.

[0004] Secondly, the traditional maintenance management system also has many shortcomings in task allocation. Since maintenance tasks involve a large number of equipment and personnel, how to efficiently and accurately allocate tasks to appropriate maintenance personnel has become an urgent problem to be solved. The traditional manual allocation method is not only inefficient, but also easily affected by subjective factors, resulting in unreasonable task allocation, which in turn affects the quality and efficiency of maintenance work.

[0005] Traditional fixed maintenance cycles may result in excessively high maintenance costs. If the maintenance cycle is set too short, unnecessary costs such as manpower and spare parts will be added. For example, frequent maintenance of equipment will consume a large amount of man-hours and spare parts, while these equipment may actually be in good operating condition. On the contrary, if the maintenance cycle is too long, the risk of equipment failure will increase. Once a failure occurs, the repair cost will usually be much higher than the regular maintenance cost, and it may also cause indirect losses such as production stagnation. Summary of the invention

[0006] The purpose of the present invention is to provide an electrical equipment maintenance management system and method, which can reduce the maintenance cost of electrical equipment and improve the maintenance efficiency.

[0007] To achieve the above objectives, in a first aspect, the present invention provides an electrical equipment maintenance management system, comprising: The maintenance plan module is used to generate a detailed task allocation plan based on the maintenance cycle and maintenance personnel information. The process includes: Set the initial pheromone concentration, maximum number of iterations, and number of ants; Defining heuristic information :

[0008] in, and is the weight coefficient, Indicates personnel To the task Skill matching degree; Indicates personnel With the task The distance of the device; No. Ants on mission When selecting Probability for:

[0009] in, and are the importance factors of pheromone and heuristic information respectively, For the moment Task Assign to personnel The pheromone concentration on the edge; Define the objective function :

[0010] in, and is the weight coefficient, is the maximum task completion time, For personnel Total time to complete assigned tasks; is the average task completion time; according to Select maintenance personnel for each task in turn, form a task allocation plan corresponding to each ant, calculate the objective function value corresponding to each ant, update the pheromone, and output the optimal solution.

[0011] Beneficial effects of the basic program: This application first dynamically generates a maintenance cycle, minimizes maintenance costs while ensuring the normal operation of the equipment, and finds the optimal balance between cost and equipment reliability. The dynamic maintenance cycle makes the allocation of maintenance tasks complicated. This technical solution uses an ant algorithm for task allocation. By simulating the foraging behavior of ants, the system can find a better allocation scheme in a complex task-personnel relationship. This method is more efficient and accurate than traditional manual allocation. In addition, the ant colony algorithm has certain potential for distributed computing and parallel processing. Ants can be regarded as multiple independent computing units, which search and update pheromones simultaneously on different paths, which enables the algorithm to utilize multi-core processors or distributed computing environments to a certain extent, improve the speed of solving task allocation schemes, and meet the needs of large-scale maintenance task allocation.

[0012] By introducing heuristic information, the skill matching degree of maintenance personnel to tasks and the distance between personnel and equipment where tasks are located are taken into account. These two factors directly affect the quality and efficiency of maintenance work. By adjusting the weight coefficient, the system can flexibly adjust the priority of these two factors according to actual conditions to ensure the rationality of task allocation.

[0013] The objective function comprehensively considers the maximum task completion time, the total time for personnel to complete the assigned tasks, and the average task completion time. By continuously optimizing the objective function value, the system can gradually approach the optimal task allocation plan, thereby shortening the maintenance cycle and reducing the maintenance cost as much as possible while ensuring the quality of maintenance, thereby significantly improving the level and efficiency of electrical equipment maintenance management.

[0014] As an implementable optimization solution, the maintenance plan module is used to receive equipment operation data and historical maintenance records of the equipment, and uses the hierarchical analysis method to construct an evaluation index system, decomposing the equipment health status assessment target into several criterion layers, and then selecting specific indicators as the indicator layer for each criterion layer, determining the weights of the indicators at each level, and then calculating the equipment health status score.

[0015] As an implementable optimization solution, the maintenance plan module dynamically generates maintenance cycles based on the equipment health status score, manufacturer recommended cycles and industry standards. The process includes: Encode the maintenance period into a chromosome, encode the chromosome according to the maximum and minimum values ​​of the maintenance period, and randomly generate the initial population; Define the objective function :

[0016]

[0017]

[0018]

[0019]

[0020] in, Indicates the labor cost of a single maintenance. Indicates The single maintenance of such equipment takes a long time. represents the average cost of spare parts for a single maintenance. Indicates The frequency factor of replacement of spare parts for this type of equipment, Indicates Maintenance cycle of such equipment, Indicates The failure rate of the equipment is obtained by fitting the historical failure data. represents the single failure repair cost, It represents the downtime loss per unit time, represents the mean time to repair; Iterate, use the roulette wheel selection method to select individuals, perform single point or crossover on individuals, and mutate them until the set number of iterations is reached or the iteration condition is met, and finally find the current optimal maintenance period.

[0021] As an implementable optimization solution, updating pheromones includes the following: set up is the pheromone enhancement constant, for the Only ants, if they choose to Assign to personnel , then the increase in pheromone on this edge is:

[0022] in, For the The objective function value obtained by only one ant; after all ants complete path selection, the total increase of pheromone on this edge is:

[0023] After each iteration, the pheromone on the path passed by the ants corresponding to the current optimal solution is increased by a certain amount; Assume that the objective function value of the elite ant is , the additional amount of pheromone is:

[0024] in, The pheromone enhancement constant for elite ants.

[0025] The updated pheromone concentration is:

[0026] in, is the pheromone volatility coefficient; As an implementable optimization solution, updating pheromones includes the following: is the adaptive pheromone volatility coefficient, and the formula is as follows:

[0027] in, and are the minimum and maximum values ​​of the pheromone volatility coefficient, is the maximum number of iterations, is the current iteration number.

[0028] As an implementable optimization solution, it also includes a process management module, which is used to push maintenance tasks, record maintenance steps, time, tools and spare parts usage data in real time, and automatically send reminder messages when the maintenance task is approaching the deadline or the key steps are not completed within the time limit; based on the maintenance records and subsequent equipment operation data, the gray correlation analysis method is used to score the maintenance quality; The various indicators under the ideal operating state of the equipment are taken as the reference sequence, and the actual operating indicators of the equipment after maintenance are taken as the comparison sequence. The maintenance quality score is obtained by calculating the correlation coefficient and correlation degree between the indicators.

[0029] As an implementable optimization solution, it also includes a fault diagnosis module for processing real-time data of equipment and using wavelet transform to extract abnormal feature vectors, including the frequency range and amplitude change of the fault.

[0030] As an implementable optimization solution, the fault diagnosis module predicts the probability of fault occurrence based on real-time data streams through long short-term memory networks. By learning from historical data, it predicts the future operating status and fault probability of equipment and triggers an alarm when the probability of fault occurrence exceeds the threshold.

[0031] As an implementable optimization solution, it also includes a status monitoring module, which is used to collect equipment parameters and generate dynamic trend charts and health status dashboards; it provides multi-dimensional data dashboards and supports multi-dimensional abnormal data drilling and analysis.

[0032] In a second aspect, the present invention provides an electrical equipment maintenance and management method, which utilizes the above-mentioned electrical equipment maintenance and management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of the architecture of the electrical equipment maintenance and management system.

[0034] Figure 2 Schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to make the technical solution and advantages of the present application clearer, the technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings. It will be understood that the specific embodiments described herein are only partial embodiments of the present invention, which are only used to explain the present application, rather than to limit the present application. It should be noted that the technical features or combinations of technical features described in the following embodiments should not be considered isolated, and they can be combined with each other to achieve better technical effects. The same reference numerals appearing in the drawings of the following embodiments represent the same features or components, which can be applied to different embodiments.

[0036] In addition, unless otherwise defined, the technical terms or scientific terms used in the description of the present invention should have the common meanings understood by those skilled in the art in the art to which the present invention belongs.

[0037] The present invention is further described in detail below in conjunction with the accompanying drawings: Reference numerals: electronic device 500 , processor 501 , communication interface 502 , memory 503 , bus 504 .

[0038] The present disclosure provides an electrical equipment maintenance management system, referring to Figure 1 , including maintenance plan module, process management module, fault diagnosis module and status monitoring module.

[0039] The maintenance plan module includes a status assessment submodule, a cycle optimization submodule, and a task allocation submodule.

[0040] The status assessment submodule is used to receive equipment operation data, including real-time parameters such as current, voltage, temperature, and historical maintenance records of the equipment. Data is collected directly from electrical equipment through sensors and stored in the system database to ensure data accuracy and timeliness.

[0041] The analytic hierarchy process (AHP) is used to construct an evaluation index system, and the equipment health status evaluation target is decomposed into criterion layers such as operating stability, failure rate, and aging degree. Then, specific indicators are selected as indicator layers for each criterion layer. For example, operating stability can be measured by indicators such as voltage fluctuation and current harmonics; failure rate is measured by the number of historical failures; aging degree can be evaluated by combining the service life of the equipment and the wear of key components. The weights of indicators at each level are determined by expert scoring or data statistics, and then the equipment health status score is calculated. The scoring range is set from 0 to 100 points. The higher the score, the better the health status of the equipment, providing a quantitative basis for subsequent maintenance decisions. The analytic hierarchy process can more accurately evaluate the actual status of the equipment by decomposing the equipment health status evaluation into multiple levels and factors, and considering their interrelationships and importance.

[0042] The cycle optimization submodule dynamically generates the optimal maintenance cycle based on the equipment health status score, and refers to the manufacturer's recommended cycle and industry standards. The cycle is dynamically adjusted according to the actual status of the equipment and various factors, avoiding the irrationality of traditional fixed cycle maintenance. The manufacturer's recommended cycle is the conventional maintenance cycle recommendation made by the equipment manufacturer based on equipment design and testing, and the industry standard is the general maintenance cycle specification formulated by the entire industry for similar equipment. The dynamic generation process is as follows: The maintenance cycle is encoded as a chromosome, the chromosome is constrained according to the maximum and minimum values ​​of the maintenance cycle (refer to the manufacturer's recommended cycle), and the initial population is randomly generated.

[0043] Define the objective function :

[0044]

[0045]

[0046]

[0047]

[0048] in, Indicates the labor cost of a single maintenance (yuan / time), Indicates Time spent on single maintenance of equipment of this type (hours), represents the average cost of spare parts for a single maintenance (yuan / time), Indicates The frequency factor of replacement of spare parts for this type of equipment, Indicates Maintenance cycle of equipment of this type (days), Indicates The failure rate of the equipment is obtained by fitting the historical failure data. represents the single failure repair cost, It represents the downtime loss per unit time, Indicates the mean time to repair.

[0049] Iterate and select individuals using the roulette wheel selection method. Perform single point or crossover on the individuals and perform mutation until the set number of iterations is reached or the iteration condition is met, and finally find the current optimal maintenance cycle.

[0050] The task allocation submodule generates a detailed task allocation plan based on the optimized cycle and maintenance personnel information, and clarifies the equipment, maintenance time and specific task content that each maintenance personnel is responsible for. Maintenance personnel information includes skill level, geographic location, and workload. Skill levels can be divided into elementary, intermediate, and advanced levels, and different levels correspond to different maintenance capabilities; geographic location is used to determine the distance between the maintenance personnel and the equipment to evaluate the response time; and workload records the amount of tasks currently undertaken by the maintenance personnel. Specifically, the task allocation plan is generated through the improved ant colony algorithm, and the generation process is as follows: Construct a graph model, take maintenance tasks and maintenance personnel as nodes in the graph, and set the maintenance task set , the maintenance personnel are assembled as , construct a bipartite graph ,in For node combination, is an edge set, edge ∈ Indicates the task Can be assigned to personnel .

[0051] Initialize and set the initial pheromone concentration , maximum number of iterations , the number of ants .

[0052] Defining heuristic information :

[0053] in, and is the weight coefficient, Indicates personnel To the task The skill matching degree ranges from [0,1]. The larger the value, the higher the matching degree. It is obtained by quantitatively calculating the skill level of the personnel and the skill level required for the task. Indicates personnel With the task The distance to the device is calculated using geographic coordinates.

[0054] No. Ants on mission When selecting Probability for:

[0055] in, and are the importance factors of pheromone and heuristic information respectively, For the moment Task Assign to personnel The pheromone concentration on the edge.

[0056] Define the objective function :

[0057] in, and is the weight coefficient, is the maximum task completion time, For personnel Total time to complete assigned tasks; is the average task completion time.

[0058] Iterate, for each ant, according to Select maintenance personnel for each task in turn, form a task allocation plan, and calculate the objective function value corresponding to each ant.

[0059] Update pheromones and set is the pheromone enhancement constant, for the Only ants, if they choose to Assign to personnel , then the increase in pheromone on this edge is:

[0060] in, For the The objective function value obtained by all ants. After all ants complete the path selection, the total increase of pheromone on this edge is:

[0061] After each iteration, the pheromone on the path passed by the ants (elite ants) corresponding to the current optimal solution is increased by a certain amount.

[0062] Assume that the objective function value of the elite ant is , the additional amount of pheromone is:

[0063] in, The pheromone enhancement constant for elite ants.

[0064] The updated pheromone concentration is:

[0065] in, is the adaptive pheromone volatility coefficient, and the formula is as follows:

[0066] in, and are the minimum and maximum values ​​of the pheromone volatility coefficient, is the maximum number of iterations, is the current iteration number, so that the convergence speed increases with the increase of iteration number.

[0067] If the maximum number of iterations is reached, the current optimal solution is output; otherwise, the iteration continues.

[0068] The process management module includes a task tracking submodule and a quality assessment submodule.

[0069] The task tracking submodule is used to push maintenance tasks. It includes functions such as task details and equipment location navigation. After receiving a task, maintenance personnel can click to view detailed maintenance steps and requirements.

[0070] It is also used to record maintenance steps, time, tools and spare parts usage data in real time. For example, during the maintenance process, each step is confirmed and the time is recorded through the task tracking submodule, and the tools and spare parts used are also entered in real time to ensure the integrity and accuracy of the data.

[0071] It is also used to automatically send reminder messages when the maintenance task is approaching the deadline or the key steps have timed out and are not completed, to ensure that the maintenance task is completed on time.

[0072] The quality assessment submodule feeds back the maintenance quality score to the maintenance plan module based on the maintenance records and subsequent equipment operation data. The maintenance plan module optimizes subsequent tasks based on the feedback results, such as adjusting the maintenance cycle and replacing maintenance personnel.

[0073] Maintenance records include various data during the maintenance process, such as the parts repaired and replaced, maintenance time, etc.; the subsequent operation data of the equipment mainly focuses on changes in failure rate, equipment performance indicators, etc.

[0074] The grey correlation analysis method is used to take the indicators under the ideal operating state of the equipment as the reference sequence, and the actual operating indicators after equipment maintenance as the comparison sequence. The maintenance quality score is obtained by calculating the correlation coefficient and correlation degree between the indicators. The score range can be set from 0 to 100 points, and the higher the score, the better the maintenance quality.

[0075] The fault diagnosis module includes a feature extraction submodule, a classification recognition submodule, and a fault warning submodule.

[0076] The feature extraction submodule is used to process the real-time data of the equipment, such as vibration frequency, power fluctuation, etc., and extract abnormal feature vectors. For example, for the vibration signal of electrical equipment, the vibration frequency and amplitude are relatively stable during normal operation. When a fault occurs, the vibration signal will fluctuate abnormally in a specific frequency band. The signal can be decomposed at different time and frequency scales. By selecting the appropriate wavelet basis function, the abnormal feature vector in the signal can be effectively extracted. The abnormal feature vector contains key information about the equipment failure, such as the frequency range and amplitude change of the fault, and performs fault classification.

[0077] The fault warning submodule predicts the probability of fault occurrence based on real-time data streams through the long short-term memory network (LSTM). The LSTM network can handle long-term dependencies in time series data, and predict the future operating status and fault probability of equipment by learning from historical data. When the probability of fault occurrence exceeds the threshold, an alarm is triggered.

[0078] The condition monitoring module includes a data monitoring submodule and a data visualization submodule.

[0079] The data monitoring submodule is used to collect equipment parameters such as current, voltage, and temperature, convert physical quantities into electrical signals through sensors, and transmit them to the system for processing. The data is stored in a time series database, which is optimized for time series data and can efficiently store and query equipment operation data. Generate dynamic trend charts and health status dashboards. The dynamic trend chart uses time as the horizontal axis and the equipment parameter value as the vertical axis to display the changing trend of equipment parameters in real time; the health status dashboard displays the overall health status of the equipment in an intuitive graphical way, such as using indicator lights of different colors to indicate the normal, warning, and fault status of the equipment.

[0080] The data visualization submodule provides a multi-dimensional data dashboard and supports abnormal data capture and analysis by device type, region, and time. For example, in the device type dimension, you can compare the operating parameters and fault conditions of different types of devices; in the region dimension, you can view the overall operating status of devices in different regions; in the time dimension, you can analyze the performance changes of devices in different time periods. When abnormal data is found, users can drill down and analyze by clicking on the data point to view more detailed device operation data and historical records, so as to quickly locate the root cause of the problem.

[0081] The disclosed embodiment also provides an electrical equipment maintenance and management method, which utilizes the above-mentioned electrical equipment maintenance and management system.

[0082] The embodiment of the present disclosure also provides a storage medium, in which a computer program is stored. When the computer program is executed by a processor, all steps of the above-mentioned electrical equipment maintenance management method can be implemented.

[0083] Those of ordinary skill in the art can understand that all or part of the processes in the electrical equipment maintenance management method can be implemented by instructing related hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of various embodiments of the electrical equipment maintenance management method. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0084] The embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned electrical equipment maintenance management method when executing the program. In the embodiment of the present application, the processor is the control center of the computer method, which can be a processor of a physical machine or a processor of a virtual machine.

[0085] Reference Figure 2 , the electronic device 500 includes: at least one processor 501, at least one communication interface 502, at least one memory 503 and at least one bus 504. The bus 504 is used to realize the connection and communication between these components, the communication interface 502 is used to communicate signaling or data with other node devices, and the memory 503 stores machine-readable instructions executable by the processor 501. When the electronic device 500 is running, the processor 501 communicates with the memory 503 through the bus 504, and when the machine-readable instructions are called by the processor 501, the steps of the above-mentioned electrical equipment maintenance management method are executed.

[0086] The above contents are only embodiments of the present invention. The common sense such as the known specific structures and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field to which the invention belongs before the application date or the priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for the ordinary technicians in the relevant field to implement this application. It should be pointed out that for the technicians in this field, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to explain the content of the claims.

Claims

1. An electrical equipment maintenance management system, characterized in that: include: The maintenance plan module is used to dynamically generate maintenance cycles and generate detailed task allocation plans based on maintenance personnel information. The process includes: Set the initial pheromone concentration, maximum number of iterations, and number of ants; Defining heuristic information : in, and is the weight coefficient, Indicates personnel To the task Skill matching degree; Indicates personnel With the task The distance of the device; No. Ants on mission When selecting Probability for: in, and are the importance factors of pheromone and heuristic information respectively, For the moment Task Assign to personnel The pheromone concentration on the edge; Define the objective function : in, and is the weight coefficient, is the maximum task completion time, For personnel Total time to complete assigned tasks; is the average task completion time; according to Select maintenance personnel for each task in turn, form a task allocation plan corresponding to each ant, calculate the objective function value corresponding to each ant, update the pheromone, and output the optimal solution.

2. The electrical equipment maintenance management system according to claim 1, characterized in that: The maintenance plan module is used to receive equipment operation data and historical maintenance records of the equipment, and uses the hierarchical analysis method to construct an evaluation index system, decompose the equipment health status evaluation target into several criterion layers, and then select specific indicators as the indicator layer for each criterion layer, determine the weights of the indicators at each level, and then calculate the equipment health status score.

3. The electrical equipment maintenance management system according to claim 1, characterized in that: The maintenance plan module dynamically generates maintenance cycles based on the equipment health status score, manufacturer recommended cycles and industry standards. The process includes: Encode the maintenance period into a chromosome, encode the chromosome according to the maximum and minimum values ​​of the maintenance period, and randomly generate the initial population; Define the objective function : in, Indicates the labor cost of a single maintenance. Indicates The single maintenance of such equipment takes a long time. represents the average cost of spare parts for a single maintenance. Indicates The frequency factor of replacement of spare parts for this type of equipment, Indicates Maintenance cycle of such equipment, Indicates The failure rate of the equipment is obtained by fitting the historical failure data. represents the single failure repair cost, It represents the downtime loss per unit time, represents the mean time to repair; Iterate, use the roulette wheel selection method to select individuals, perform single point or crossover on individuals, and mutate them until the set number of iterations is reached or the iteration condition is met, and finally find the current optimal maintenance period.

4. The electrical equipment maintenance management system according to claim 1, characterized in that: Updated pheromones include the following: set up is the pheromone enhancement constant, for the Only ants, if they choose to Assign to personnel , then the increase in pheromone on this edge is: in, For the The objective function value obtained by only one ant; after all ants complete path selection, the total increase of pheromone on this edge is: After each iteration, the pheromone on the path passed by the ants corresponding to the current optimal solution is increased by a certain amount; Assume that the objective function value of the elite ant is , the additional amount of pheromone is: in, Enhance constants for elite ant pheromones; The updated pheromone concentration is: in, is the pheromone volatility coefficient.

5. The electrical equipment maintenance management system according to claim 4, characterized in that: Updated pheromones include the following: is the adaptive pheromone volatility coefficient, and the formula is as follows: in, and are the minimum and maximum values ​​of the pheromone volatility coefficient, is the maximum number of iterations, is the current iteration number.

6. The electrical equipment maintenance management system according to claim 1, characterized in that: It also includes a process management module, which is used to push maintenance tasks, record maintenance steps, time, tools and spare parts usage data in real time, and automatically send reminder messages when the maintenance task is approaching the deadline or the key steps are not completed within the time limit; based on the maintenance records and subsequent equipment operation data, the maintenance quality is scored using the grey correlation analysis method; The various indicators under the ideal operating state of the equipment are taken as the reference sequence, and the actual operating indicators of the equipment after maintenance are taken as the comparison sequence. The maintenance quality score is obtained by calculating the correlation coefficient and correlation degree between the indicators.

7. The electrical equipment maintenance management system according to claim 1, characterized in that: It also includes a fault diagnosis module for processing real-time data of equipment and using wavelet transform to extract abnormal feature vectors, including the frequency range and amplitude changes of fault occurrence.

8. The electrical equipment maintenance management system according to claim 7, characterized in that: The fault diagnosis module is based on real-time data streams and predicts the probability of faults through long-short-term memory networks. By learning from historical data, it predicts the future operating status and fault probability of equipment and triggers an alarm when the probability of faults exceeds the threshold.

9. The electrical equipment maintenance management system according to claim 1, characterized in that: It also includes a status monitoring module for collecting equipment parameters and generating dynamic trend charts and health status dashboards; it provides multi-dimensional data dashboards and supports multi-dimensional abnormal data drilling and analysis.

10. A method for maintenance and management of electrical equipment, characterized in that: An electrical equipment maintenance and management system as described in any one of claims 1 to 9 is used.

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