Intelligent operation and maintenance method and system based on power distribution cabinet

Abstract

The invention relates to an intelligent operation and maintenance method and system based on power distribution cabinets, and relates to the field of equipment operation and maintenance technologies, and the method comprises the steps: obtaining a previous operation and maintenance point of each power distribution cabinet; constructing a demand analysis interval according to the current time point and the previous operation and maintenance point, and delimiting a unit interval according to a preset unit duration in the demand analysis interval; acquiring unit environment parameters in each unit interval, and determining unit pressure-bearing coefficients corresponding to the unit environment parameters according to a preset pressure-bearing matching relationship; calculating according to all the unit pressure-bearing coefficients to determine an overall pressure-bearing coefficient, and defining the power distribution cabinet of which the overall pressure-bearing coefficient is greater than a preset demand operation and maintenance coefficient as an inspection cabinet; and generating an overall inspection scheme according to all the inspection cabinets, and outputting the overall inspection scheme to a preset management end. The power distribution cabinet inspection system has the effect of improving the overall inspection efficiency of workers on the power distribution cabinet.

Description

Technical Field

[0001] This application relates to the field of equipment operation and maintenance technology, and in particular to an intelligent operation and maintenance method and system based on power distribution cabinets. Background Technology

[0002] As the core equipment for power distribution and control, the stable and reliable operation of distribution cabinets is crucial for ensuring the power supply of industrial production, commercial activities, and public facilities. To ensure the normal use of distribution cabinets and prevent potential failures, the traditional maintenance method is to conduct regular manual inspections. This method typically involves uniformly inspecting, testing, and maintaining all distribution cabinets at fixed time intervals, including visual inspection, temperature measurement, fastener condition, instrument readings, and environmental conditions.

[0003] However, in practical applications, the installation locations of distribution cabinets vary widely, and the actual environmental conditions differ significantly. These different environmental factors directly affect the aging rate of internal components, the degree of insulation degradation, contact point oxidation, and mechanical component wear. For example, distribution cabinets in high-temperature and high-humidity environments face a much higher risk of component aging and connection point corrosion than those in clean, temperature-controlled environments. Therefore, a fixed inspection frequency leads to more ineffective checks by staff within the same timeframe, resulting in low overall inspection efficiency and room for improvement. Summary of the Invention

[0004] To improve the overall inspection efficiency of power distribution cabinets by staff, this application provides an intelligent operation and maintenance method and system based on power distribution cabinets.

[0005] Firstly, this application provides an intelligent operation and maintenance method based on a power distribution cabinet, employing the following technical solution: A smart operation and maintenance method based on power distribution cabinets includes: Obtain the previous maintenance point for each power distribution cabinet; The demand analysis interval is constructed based on the current time point and the previous operation and maintenance point, and the unit interval is divided under the demand analysis interval according to the preset unit duration. Unit environmental parameters are obtained in each unit interval, and the unit bearing pressure coefficient corresponding to the unit environmental parameters is determined according to the preset bearing pressure matching relationship. The overall pressure coefficient is determined by calculating based on all unit pressure coefficients, and the distribution cabinet with an overall pressure coefficient greater than the preset required maintenance coefficient is defined as an inspection cabinet. Generate an overall inspection plan based on all inspection cabinets, and output the overall inspection plan to the preset management terminal.

[0006] Optionally, it also includes a step for determining the demand maintenance coefficient, which includes: Construct a historical interval on a preset timeline with the current time point as the endpoint and a width of a preset historical duration, and determine the operation and maintenance pressure coefficient and equipment detection status of each distribution cabinet within the historical interval; The maintenance pressure coefficient when the equipment detection status is consistent with the preset equipment maintenance status is defined as the investigation pressure coefficient, and the investigation similar range is constructed under each investigation pressure coefficient based on the preset similar coefficient; The number of internal investigations is determined by counting the pressure coefficients of investigations within the same investigation range, and the number of external investigations is determined by counting the maintenance pressure coefficients of those within the same investigation range that are not investigation pressure coefficients. The critical suitable value is determined by calculating the number of internal and external investigations, and the range of investigations with the largest critical suitable value is defined as the pressure critical range. The required operation and maintenance coefficient is determined by calculating the operation and maintenance pressure coefficient within the pressure critical range.

[0007] Optionally, the steps for calculating the required maintenance factor based on the maintenance pressure factor within the critical pressure range include: A simulated operation and maintenance coefficient is randomly generated within the critical pressure range. The investigation and handling deviation coefficient is determined based on the simulated operation and maintenance coefficient and the investigation and handling pressure coefficient. The operation and maintenance deviation coefficient is determined based on the simulated operation and maintenance coefficient and the operation and maintenance pressure coefficient that is not the investigation and handling pressure coefficient. The suitability of the simulation is determined by calculating the investigation deviation coefficient, the preset investigation weight coefficient, the operation and maintenance deviation coefficient, and the preset operation and maintenance weight coefficient. The simulation suitability with the largest value is determined according to the preset sorting rules, and the simulation operation and maintenance coefficient corresponding to the simulation suitability is defined as the critical operation and maintenance coefficient. The required operation and maintenance coefficient is determined by calculating based on the critical operation and maintenance coefficient and the preset adjustment coefficient.

[0008] Optionally, the method may also include a step for determining the adjustment coefficient, which includes: The maximum simulated suitability is defined as the upper limit suitability, and a range of similar upper limit suitability is constructed based on the upper limit suitability and the preset similar suitability. The simulation operation and maintenance coefficient that is close to the upper limit in terms of simulation suitability is defined as the upper limit proximity coefficient, and the critical deviation coefficient is determined by calculating the difference between the upper limit proximity coefficient and the critical operation and maintenance coefficient. The critical deviation coefficient with the largest value is determined according to the sorting rules, and this critical deviation coefficient is determined as the adjustment coefficient.

[0009] Optionally, after the suitability of the simulation is determined, the intelligent operation and maintenance method based on the power distribution cabinet also includes: Determine whether there exist at least two simulations with the same suitability and the largest simulation operation and maintenance coefficient; If there are no at least two simulations with the same and largest simulation suitability, then the simulation operation and maintenance coefficient corresponding to the largest simulation suitability is defined as the critical operation and maintenance coefficient. If there are at least two simulation operation and maintenance coefficients with the same and the largest simulation suitability, then the simulation operation and maintenance coefficient corresponding to the largest simulation suitability is defined as the alternative operation and maintenance coefficient. The candidate unit interval is constructed by calculating the candidate maintenance coefficient and the preset unit coefficient, and the unit suitability is determined by calculating the simulation suitability of each simulated maintenance coefficient within the candidate unit interval. The unit suitability with the largest value is determined according to the sorting rules, and the alternative operation and maintenance coefficient corresponding to this unit suitability is defined as the critical operation and maintenance coefficient.

[0010] Optionally, the steps for generating an overall inspection plan based on all inspection cabinets include: Obtain the inspection location points based on each inspection cabinet; The inspection locations are randomly ordered to construct a simulated inspection sequence, and the position movement distance between adjacent inspection locations in the simulated inspection sequence is determined based on the simulated inspection sequence. The overall inspection route is determined by summing all the location movement distances, and an overall inspection plan is generated based on the simulated inspection sequence corresponding to the minimum overall inspection route.

[0011] Optionally, after the overall inspection route is determined, the intelligent operation and maintenance method based on the power distribution cabinet also includes: In the simulated inspection sequence, the adjacent inspection position point in front is defined as the preceding position point, and the inspection position point behind is defined as the following position point; The number of common detections is determined by counting based on the overall inspection scheme that includes the preceding and subsequent position points within the historical interval, and the number of similar detections is determined by counting based on the overall inspection scheme that the preceding position point is in front of the subsequent position point. The similarity detection ratio is determined by calculating the number of similar detections and the number of common detections, and the relative reliability coefficient corresponding to the similarity detection ratio is determined by the preset reliable matching relationship. The distance correction factor is determined based on all the relative reliability factors, and the overall inspection distance is calculated and updated based on the distance correction factor.

[0012] Secondly, this application provides an intelligent operation and maintenance system based on a power distribution cabinet, which adopts the following technical solution: An intelligent operation and maintenance system based on a power distribution cabinet includes: The acquisition module is used to acquire the previous maintenance point of each power distribution cabinet; The processing module, connected to the acquisition and judgment modules, is used for information storage and processing; The judgment module, connected to the acquisition and processing modules, is used for judging information. The processing module constructs a demand analysis interval based on the current time point and the previous operation and maintenance point, and divides the unit interval under the demand analysis interval according to the preset unit duration. The acquisition module acquires unit environmental parameters in each unit interval, and the processing module determines the unit pressure coefficient corresponding to the unit environmental parameters according to the preset pressure matching relationship. The processing module calculates the overall pressure coefficient based on all unit pressure coefficients and defines the distribution cabinets whose overall pressure coefficient determined by the judgment module is greater than the preset required maintenance coefficient as inspection cabinets. The processing module generates an overall inspection plan based on all inspection cabinets and outputs the overall inspection plan to the preset management terminal.

[0013] In summary, this application includes at least one of the following beneficial technical effects: During the operation and maintenance management of each distribution cabinet, the theoretical pressure bearing coefficient of each distribution cabinet is analyzed and determined to identify the distribution cabinets that need operation and maintenance. This allows staff to perform operation and maintenance on the distribution cabinets more accurately, thereby improving the overall inspection efficiency of the distribution cabinets. In analyzing whether power distribution cabinets require maintenance, appropriate analytical data is formulated based on the specific circumstances of each cabinet to improve the accuracy of the data analysis. Attached Figure Description

[0014] Figure 1 This is a flowchart of an intelligent operation and maintenance method based on power distribution cabinets.

[0015] Figure 2 This is a module flowchart of an intelligent operation and maintenance method based on power distribution cabinets. Detailed Implementation

[0016] To make the purpose, technical solution, and advantages of this application clearer, the following is combined with Figures 1-2 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0017] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0018] This application discloses an intelligent operation and maintenance method based on a power distribution cabinet, referring to... Figure 1 The method flow of intelligent operation and maintenance based on power distribution cabinets includes the following steps: Step S100: Obtain the previous maintenance point of each power distribution cabinet.

[0019] The previous maintenance point is the time when the power distribution cabinet was last maintained.

[0020] Step S101: Construct a demand analysis interval based on the current time point and the previous operation and maintenance point, and define unit intervals under the demand analysis interval according to the preset unit duration.

[0021] The demand analysis interval is the time interval between the previous operation and maintenance point and the current time point. Generally, the time point records in this application are in days, and the unit duration is one day, or 24 hours. The unit interval is the time interval corresponding to each day in the demand analysis interval.

[0022] Step S102: Obtain the unit environmental parameters in each unit interval, and determine the unit pressure coefficient corresponding to the unit environmental parameters according to the preset pressure matching relationship.

[0023] The unit environmental parameter refers to the parameter value of the environment in which the distribution cabinet is located within a unit range, such as high temperature, low humidity, and low load. The unit environmental parameter can be obtained by setting relevant parameters and setting corresponding sensors by the staff. The unit pressure coefficient is the damage coefficient that the distribution cabinet will suffer in terms of lifespan under the current unit environmental parameters. This value can reflect the impact of the environment on the operation and maintenance of the distribution cabinet. Different unit environmental parameters have different impacts on the distribution cabinet, so the corresponding unit pressure coefficient is also different. The pressure matching relationship between the two is determined by the staff in advance through multiple tests, which will not be elaborated here.

[0024] Step S103: Calculate the overall pressure coefficient based on all unit pressure coefficients, and define the distribution cabinet with an overall pressure coefficient greater than the preset required maintenance coefficient as an inspection cabinet.

[0025] The overall pressure bearing coefficient is the sum of all unit pressure bearing coefficients. The required maintenance coefficient is the minimum overall pressure bearing coefficient required when the current distribution cabinet needs maintenance. This value can be set in advance by the staff or determined according to the method of steps S200-S203, which will not be elaborated here. At this time, the inspection cabinet is defined to identify and distinguish the distribution cabinets that need to be inspected for maintenance, which will facilitate subsequent analysis.

[0026] Step S104: Generate an overall inspection plan based on all inspection cabinets and output the overall inspection plan to the preset management terminal.

[0027] The overall inspection plan is a plan that can inspect and process all inspection cabinets. The inspection cabinets can be randomly sorted to construct the overall inspection plan, or the overall inspection plan can be determined through steps S600-S602. At this time, the overall inspection plan can be output to the management terminal to provide reference for the staff.

[0028] It also includes the step of determining the demand maintenance coefficient, which includes: Step S200: Construct a historical interval on the preset time axis with the current time point as the end point and the width as the preset historical duration, and determine the operation and maintenance pressure coefficient and equipment detection status of each distribution cabinet within the historical interval.

[0029] The time axis is a coordinate axis formed by combining various time points. This coordinate axis points from the time points that have already passed to the time points that have not yet been reached. The time points that have already passed are on the left side, and the left side is defined as the front end. The historical duration is the duration for which staff can obtain historical data for each distribution cabinet. Historical intervals are constructed to facilitate the acquisition and analysis of data within the historical duration. The maintenance pressure coefficient is the overall pressure coefficient of the distribution cabinet corresponding to the maintenance treatment performed by staff within the historical interval. The equipment detection status is the status entered by staff after inspection to determine whether the equipment is damaged.

[0030] Step S201: Define the maintenance pressure coefficient when the equipment detection status is consistent with the preset equipment maintenance status as the investigation pressure coefficient, and construct the investigation similar range under each investigation pressure coefficient according to the preset similar coefficient.

[0031] The equipment maintenance status is the equipment detection status set by the staff when they determine that the distribution cabinet is damaged and needs maintenance. By defining the inspection pressure coefficient, the maintenance pressure coefficients of the current distribution cabinet in the past when it was damaged are identified and distinguished, which is convenient for subsequent analysis. The similarity coefficient is the maximum allowable difference when the staff determines that two inspection pressure coefficients are close to each other. The inspection similarity range is determined by adding and subtracting the similarity coefficient from the inspection pressure coefficient.

[0032] Step S202: Count the internal quantity of investigations based on the pressure coefficient of investigations within the same investigation range, and count the external quantity of investigations based on the maintenance pressure coefficient of maintenance personnel within the same investigation range that is not an investigation pressure coefficient.

[0033] The internal number of cases investigated refers to the number of cases with pressure coefficients within the same investigation range, while the external number of cases investigated refers to the number of maintenance pressure coefficients within the same investigation range that are not subject to investigation.

[0034] Step S203: Calculate and determine the critical suitable value based on the number of internal and external investigations, and define the investigation range with the largest critical suitable value as the pressure critical range. Calculate the required operation and maintenance coefficient based on the operation and maintenance pressure coefficient within the pressure critical range.

[0035] The critical suitability value reflects whether the currently determined investigation and handling range adequately covers the critical point state of the current distribution cabinet requiring maintenance or not requiring maintenance. A larger value indicates that the current investigation and handling range more comprehensively covers the critical state. The formula for calculating the critical suitability value is as follows: ,in For the critical suitable value, In order to investigate the internal quantity, In order to investigate external quantities, The preset weighting parameters are used to calculate the importance of internal investigation quantities relative to the critical appropriate value. The preset calculation weight parameter reflects the importance of the number of external investigations to the determination of the critical appropriate value. At this time, the maximum critical appropriate value indicates whether the current distribution cabinet needs to be inspected and is within the range of investigations. Therefore, the pressure-bearing critical range is defined for identification and differentiation. At this time, the maintenance pressure coefficient within the pressure-bearing critical range can be used to determine the required maintenance coefficient, so that each distribution cabinet can determine the appropriate required maintenance coefficient according to its own actual situation and historical maintenance situation, thereby improving the accuracy of distribution cabinet maintenance analysis. The specific method for determining the required maintenance coefficient can be referred to steps S300-S302.

[0036] The steps for calculating the required maintenance factor based on the maintenance pressure coefficient within the critical pressure range include: Step S300: Randomly generate a simulated operation and maintenance coefficient within the critical pressure range, and calculate and determine the investigation deviation coefficient based on the simulated operation and maintenance coefficient and the investigation pressure coefficient. Also, calculate and determine the operation and maintenance deviation coefficient based on the simulated operation and maintenance coefficient and the operation and maintenance pressure coefficient that is not the investigation pressure coefficient.

[0037] By constructing simulated operation and maintenance coefficients, various data within the critical pressure range can be analyzed; the investigation deviation coefficient is the difference between the simulated operation and maintenance coefficient and the investigation pressure coefficient, and this difference is an absolute value; the operation and maintenance deviation coefficient is the difference between the simulated operation and maintenance coefficient and the operation and maintenance pressure coefficient that is not the investigation pressure coefficient, and this difference is also an absolute value.

[0038] Step S301: Calculate the simulation suitability based on the investigation deviation coefficient, the preset investigation weight coefficient, the operation and maintenance deviation coefficient, and the preset operation and maintenance weight coefficient.

[0039] Simulation suitability is a numerical value reflecting whether the set simulated operation and maintenance coefficients can effectively distinguish between the pressure coefficients that are not identified and the pressure coefficients that are not identified. In other words, it's a value used to determine whether maintenance is needed. The calculation formula is as follows: ,in To simulate suitability, In order to investigate the weighting coefficient, This is the operation and maintenance weighting coefficient. These are preset fixed calculation parameters. For the first Individual investigation deviation coefficient, For the first The pressure coefficient of operation and maintenance is not investigated and dealt with.

[0040] Step S302: Determine the simulation suitability with the largest value according to the preset sorting rules, and define the simulation operation and maintenance coefficient corresponding to the simulation suitability as the critical operation and maintenance coefficient. Calculate the required operation and maintenance coefficient based on the critical operation and maintenance coefficient and the preset adjustment coefficient.

[0041] The sorting rule is a method set by the staff that has the function of comparing numerical values, such as the bubble sort method. The sorting rule can determine the suitability of the simulation with the largest value, which means that the corresponding simulation operation and maintenance coefficient can better reflect the critical state of whether the distribution cabinet needs operation and maintenance. Therefore, a critical operation and maintenance coefficient is defined to identify and distinguish different simulation operation and maintenance coefficients. The adjustment coefficient is an adjustment value introduced to the critical operation and maintenance coefficient to reduce the omission of analysis. By subtracting the adjustment coefficient from the critical operation and maintenance coefficient, the appropriate required operation and maintenance coefficient can be better determined.

[0042] It also includes a step for determining the adjustment coefficient, which includes: Step S400: Define the maximum simulated suitability as the upper limit suitability, and calculate the upper limit similarity range based on the upper limit suitability and the preset similarity suitability.

[0043] The upper limit of suitability is defined to identify and distinguish the maximum simulated suitability, which facilitates subsequent analysis. The similarity suitability is the maximum difference allowed when two simulated suitability values ​​are considered to be close, as set by the staff. The lower limit value can be determined by subtracting the similarity suitability from the upper limit suitability. At this time, the upper limit suitability can be used as the upper limit suitability to construct the upper limit similarity range.

[0044] Step S401: Define the simulation operation and maintenance coefficient that is close to the upper limit as the upper limit proximity coefficient, and calculate the difference between the upper limit proximity coefficient and the critical operation and maintenance coefficient to determine the critical deviation coefficient.

[0045] Define an upper limit proximity coefficient to identify and distinguish simulated operation and maintenance coefficients that are close to the upper limit suitability in terms of simulated suitability; the critical deviation coefficient is the difference between the upper limit proximity coefficient and the critical operation and maintenance coefficient, and this difference is an absolute value.

[0046] Step S402: Determine the critical deviation coefficient with the largest value according to the sorting rules, and determine the critical deviation coefficient as the adjustment coefficient.

[0047] At this point, the maximum critical deviation coefficient can better reflect the adjustment coefficient for reducing omissions in judgments, so normal definition analysis can be performed.

[0048] After the suitability of the simulation is determined, the intelligent operation and maintenance method based on the power distribution cabinet also includes: Step S500: Determine whether there are at least two simulations with the same suitability and the largest simulation operation and maintenance coefficient.

[0049] The purpose of this judgment is to determine whether there are multiple simulated operation and maintenance coefficients that meet the requirements, so as to determine the critical operation and maintenance coefficient.

[0050] Step S5001: If there are no at least two simulation fitness coefficients that are the same and have the largest simulation fitness coefficient, then the simulation fitness coefficient corresponding to the largest simulation fitness coefficient is defined as the critical fitness coefficient.

[0051] When there are no at least two simulation operation and maintenance coefficients with the same and largest suitability, it means that there is only one simulation operation and maintenance coefficient that meets the requirements. In this case, it can be defined as the critical operation and maintenance coefficient.

[0052] Step S5002: If there are at least two simulation operation and maintenance coefficients with the same and the largest simulation suitability, then the simulation operation and maintenance coefficient corresponding to the largest simulation suitability is defined as the alternative operation and maintenance coefficient.

[0053] When there are at least two simulation operation and maintenance coefficients with the same and largest suitability, it indicates that there are multiple simulation operation and maintenance coefficients that meet the requirements and require further analysis. Therefore, alternative operation and maintenance coefficients are defined to distinguish different simulation operation and maintenance coefficients for the convenience of subsequent analysis.

[0054] Step S501: Calculate the candidate operation and maintenance coefficients and the preset unit coefficients to construct the candidate unit interval, and calculate the unit suitability based on the simulation suitability of each simulated operation and maintenance coefficient in the candidate unit interval.

[0055] The unit coefficient is a fixed value set by the staff. The candidate unit interval can be constructed by adding and subtracting the unit coefficient from the candidate maintenance coefficients. The unit suitability is the average of the simulated suitability of each simulated maintenance coefficient within the candidate unit interval.

[0056] Step S502: Determine the unit suitability with the largest value according to the sorting rules, and define the candidate operation and maintenance coefficient corresponding to the unit suitability as the critical operation and maintenance coefficient.

[0057] The maximum unit suitability can be determined by the sorting rules, which means that the corresponding alternative operation and maintenance coefficient under this unit suitability is more in line with the requirements. Therefore, it can be defined as the critical operation and maintenance coefficient.

[0058] The steps for generating an overall inspection plan based on all inspection cabinets include: Step S600: Obtain the inspection location points according to each inspection cabinet.

[0059] The inspection location point is the actual location of each inspection cabinet in the physical space.

[0060] Step S601: Randomly sort the inspection location points to construct a simulated inspection order, and determine the position movement distance between adjacent inspection location points in the simulated inspection order according to the simulated inspection order.

[0061] The simulated inspection sequence is the order of the inspection cabinets obtained by randomly sorting the inspection locations, which is also the simulated order of operation and maintenance of each inspection cabinet; the location movement distance is the shortest distance that the staff needs to travel when moving between adjacent inspection locations in the simulated inspection sequence, which can be analyzed on the map where the staff can walk.

[0062] Step S602: Sum the distances of all position movements to determine the overall inspection route, and generate an overall inspection plan based on the simulated inspection sequence corresponding to the minimum overall inspection route.

[0063] The overall inspection route is the shortest distance required for staff to perform maintenance on all inspection cabinets according to the simulated inspection sequence. It is determined by adding up the distances of all location movements. The minimum overall inspection route indicates the most convenient inspection for staff. Therefore, the corresponding simulated inspection sequence and the corresponding inspection cabinets can be combined to construct an overall inspection plan for staff reference.

[0064] After the overall inspection route is determined, the intelligent operation and maintenance method based on the power distribution cabinet also includes: Step S700: In the simulated inspection sequence, the adjacent inspection position point in front is defined as the preceding position point, and the inspection position point behind is defined as the following position point.

[0065] Define preceding and subsequent position points to identify and distinguish different inspection position points, which will facilitate subsequent analysis.

[0066] Step S701: Count the number of common detections in the historical interval according to the overall inspection scheme that includes the preceding position point and the following position point, and count the number of similar detections according to the overall inspection scheme that the preceding position point is in front of the following position point.

[0067] The number of joint detections refers to the number of overall inspection schemes that simultaneously check both the preceding and following position points in the historical interval; the number of similar detections refers to the number of overall inspection schemes in the historical interval where the preceding and following position points are in the same overall inspection scheme, and the sequential arrangement of the preceding and following position points is consistent with the current situation.

[0068] Step S702: Calculate the similarity detection ratio based on the number of similar detections and the number of common detections, and determine the relative reliability coefficient corresponding to the similarity detection ratio based on the preset reliable matching relationship.

[0069] The similarity detection ratio is the value of the number of similar detections divided by the number of common detections. The relative reliability coefficient is the value that reflects the reasonableness of the current arrangement of the preceding and following position points. The larger the similarity detection ratio, the larger the corresponding relative reliability coefficient. The reliable matching relationship between the two is determined by the staff in advance through multiple experiments, which will not be elaborated here.

[0070] Step S703: Calculate and determine the route correction factor based on all the relative reliability factors, and calculate and update the overall inspection route based on the route correction factor.

[0071] The route correction factor is the sum of all relative reliability factors. The overall inspection route can be updated by subtracting the route correction factor from the overall inspection route. Thus, by analyzing the overall inspection route, a suitable overall inspection plan can be determined.

[0072] Reference Figure 2 Based on the same inventive concept, embodiments of the present invention provide an intelligent operation and maintenance system based on a power distribution cabinet, comprising: The acquisition module is used to acquire the previous maintenance point of each power distribution cabinet; The processing module, connected to the acquisition and judgment modules, is used for information storage and processing; The judgment module, connected to the acquisition and processing modules, is used for judging information. The processing module constructs a demand analysis interval based on the current time point and the previous operation and maintenance point, and divides the unit interval under the demand analysis interval according to the preset unit duration. The acquisition module acquires unit environmental parameters in each unit interval, and the processing module determines the unit pressure coefficient corresponding to the unit environmental parameters according to the preset pressure matching relationship. The processing module calculates the overall pressure coefficient based on all unit pressure coefficients and defines the distribution cabinets whose overall pressure coefficient determined by the judgment module is greater than the preset required maintenance coefficient as inspection cabinets. The processing module generates an overall inspection plan based on all inspection cabinets and outputs the overall inspection plan to the preset management terminal; The demand maintenance coefficient determination module is used to determine the demand maintenance coefficient of each power distribution cabinet; The critical pressure range analysis module is used to analyze the critical pressure range to determine the required operation and maintenance coefficient; The adjustment coefficient determination module is used to determine the adjustment coefficients for each distribution cabinet. The simulated operation and maintenance coefficient filtering module is used to filter multiple simulated operation and maintenance coefficients that meet the requirements. The overall inspection plan generation module is used to generate overall inspection plans for each inspection point. The overall inspection route update module is used to update the overall inspection route.

[0073] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

Claims

1. A smart operation and maintenance method based on a power distribution cabinet, characterized in that, include: Obtain the previous maintenance point for each power distribution cabinet; The demand analysis interval is constructed based on the current time point and the previous operation and maintenance point, and the unit interval is divided under the demand analysis interval according to the preset unit duration. Unit environmental parameters are obtained in each unit interval, and the unit bearing pressure coefficient corresponding to the unit environmental parameters is determined according to the preset bearing pressure matching relationship. The overall pressure coefficient is determined by calculating based on all unit pressure coefficients, and the distribution cabinet with an overall pressure coefficient greater than the preset required maintenance coefficient is defined as an inspection cabinet. Generate an overall inspection plan based on all inspection cabinets, and output the overall inspection plan to the preset management terminal.

2. The intelligent operation and maintenance method based on power distribution cabinet according to claim 1, characterized in that, It also includes the step of determining the demand maintenance coefficient, which includes: Construct a historical interval on a preset timeline with the current time point as the endpoint and a width of a preset historical duration, and determine the operation and maintenance pressure coefficient and equipment detection status of each distribution cabinet within the historical interval; The maintenance pressure coefficient when the equipment detection status is consistent with the preset equipment maintenance status is defined as the investigation pressure coefficient, and the investigation similar range is constructed under each investigation pressure coefficient based on the preset similar coefficient; The number of internal investigations is determined by counting the pressure coefficients of investigations within the same investigation range, and the number of external investigations is determined by counting the maintenance pressure coefficients of those within the same investigation range that are not investigation pressure coefficients. The critical suitable value is determined by calculating the number of internal and external investigations, and the range of investigations with the largest critical suitable value is defined as the pressure critical range. The required operation and maintenance coefficient is determined by calculating the operation and maintenance pressure coefficient within the pressure critical range.

3. The intelligent operation and maintenance method based on power distribution cabinet according to claim 2, characterized in that, The steps for calculating the required maintenance factor based on the maintenance pressure coefficient within the critical pressure range include: A simulated operation and maintenance coefficient is randomly generated within the critical pressure range. The investigation and handling deviation coefficient is determined based on the simulated operation and maintenance coefficient and the investigation and handling pressure coefficient. The operation and maintenance deviation coefficient is determined based on the simulated operation and maintenance coefficient and the operation and maintenance pressure coefficient that is not the investigation and handling pressure coefficient. The suitability of the simulation is determined by calculating the investigation deviation coefficient, the preset investigation weight coefficient, the operation and maintenance deviation coefficient, and the preset operation and maintenance weight coefficient. The simulation suitability with the largest value is determined according to the preset sorting rules, and the simulation operation and maintenance coefficient corresponding to the simulation suitability is defined as the critical operation and maintenance coefficient. The required operation and maintenance coefficient is determined by calculating based on the critical operation and maintenance coefficient and the preset adjustment coefficient.

4. The intelligent operation and maintenance method based on power distribution cabinet according to claim 3, characterized in that, It also includes a step for determining the adjustment coefficient, which includes: The maximum simulated suitability is defined as the upper limit suitability, and a range of similar upper limit suitability is constructed based on the upper limit suitability and the preset similar suitability. The simulation operation and maintenance coefficient that is close to the upper limit in terms of simulation suitability is defined as the upper limit proximity coefficient, and the critical deviation coefficient is determined by calculating the difference between the upper limit proximity coefficient and the critical operation and maintenance coefficient. The critical deviation coefficient with the largest value is determined according to the sorting rules, and this critical deviation coefficient is determined as the adjustment coefficient.

5. The intelligent operation and maintenance method based on power distribution cabinet according to claim 3, characterized in that, After the suitability of the simulation is determined, the intelligent operation and maintenance method based on the power distribution cabinet also includes: Determine whether there exist at least two simulations with the same suitability and the largest simulation operation and maintenance coefficient; If there are no at least two simulations with the same and largest simulation suitability, then the simulation operation and maintenance coefficient corresponding to the largest simulation suitability is defined as the critical operation and maintenance coefficient. If there are at least two simulation operation and maintenance coefficients with the same and the largest simulation suitability, then the simulation operation and maintenance coefficient corresponding to the largest simulation suitability is defined as the alternative operation and maintenance coefficient. The candidate unit interval is constructed by calculating the candidate maintenance coefficient and the preset unit coefficient, and the unit suitability is determined by calculating the simulation suitability of each simulated maintenance coefficient within the candidate unit interval. The unit suitability with the largest value is determined according to the sorting rules, and the alternative operation and maintenance coefficient corresponding to this unit suitability is defined as the critical operation and maintenance coefficient.

6. The intelligent operation and maintenance method based on power distribution cabinet according to claim 2, characterized in that, The steps for generating an overall inspection plan based on all inspection cabinets include: Obtain the inspection location points based on each inspection cabinet; The inspection locations are randomly ordered to construct a simulated inspection sequence, and the position movement distance between adjacent inspection locations in the simulated inspection sequence is determined based on the simulated inspection sequence. The overall inspection route is determined by summing all the location movement distances, and an overall inspection plan is generated based on the simulated inspection sequence corresponding to the minimum overall inspection route.

7. The intelligent operation and maintenance method based on power distribution cabinet according to claim 6, characterized in that, After the overall inspection route is determined, the intelligent operation and maintenance method based on the power distribution cabinet also includes: In the simulated inspection sequence, the adjacent inspection position point in front is defined as the preceding position point, and the inspection position point behind is defined as the following position point; The number of common detections is determined by counting based on the overall inspection scheme that includes the preceding and subsequent position points within the historical interval, and the number of similar detections is determined by counting based on the overall inspection scheme that the preceding position point is in front of the subsequent position point. The similarity detection ratio is determined by calculating the number of similar detections and the number of common detections, and the relative reliability coefficient corresponding to the similarity detection ratio is determined by the preset reliable matching relationship. The distance correction factor is determined based on all the relative reliability factors, and the overall inspection distance is calculated and updated based on the distance correction factor.

8. An intelligent operation and maintenance system based on a power distribution cabinet, characterized in that, include: The acquisition module is used to acquire the previous maintenance point of each power distribution cabinet; The processing module, connected to the acquisition and judgment modules, is used for information storage and processing; The judgment module, connected to the acquisition and processing modules, is used for judging information. The processing module constructs a demand analysis interval based on the current time point and the previous operation and maintenance point, and divides the unit interval under the demand analysis interval according to the preset unit duration. The acquisition module acquires unit environmental parameters in each unit interval, and the processing module determines the unit pressure coefficient corresponding to the unit environmental parameters according to the preset pressure matching relationship. The processing module calculates the overall pressure coefficient based on all unit pressure coefficients and defines the distribution cabinets whose overall pressure coefficient determined by the judgment module is greater than the preset required maintenance coefficient as inspection cabinets. The processing module generates an overall inspection plan based on all inspection cabinets and outputs the overall inspection plan to the preset management terminal.

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