A power equipment inspection management system

Abstract

The application discloses a kind of suitable for power equipment inspection management system, it is related to power equipment inspection technical field, data acquisition module obtains the target information of the power equipment to be detected, the target information at least includes historical failure data;Region determination module determines the region to be detected based on the historical failure data of detection power equipment, and each inspection point in the region to be detected and each inspection point corresponding inspection component are determined synchronously, the region to be detected includes high failure area and low failure area, the present application is helpful to solve the problems, such as low efficiency, high risk of missed detection, difficult fault correlation judgment, etc.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power equipment inspection, and particularly relates to a power equipment inspection management system. BACKGROUND

[0002] Power inspection is daily inspection and maintenance of power equipment, and specific inspection devices are required for power inspection;

[0003] In daily operation of a power system, a power distribution cabinet is a core hub of power distribution and control, and stable operation of the power distribution cabinet is directly related to reliability of the entire power network. However, the traditional power distribution cabinet inspection mode has many disadvantages: on the one hand, a targeted inspection plan is lacked, resulting in low inspection efficiency and consumption of a large amount of manpower and time cost; on the other hand, it is difficult to predict potential risk areas according to historical fault information, and missed inspection is prone to occur, so that hidden faults cannot be found in time; in addition, when a component fault is detected, other potential fault components cannot be quickly associated and judged, and accurate maintenance cannot be achieved. SUMMARY

[0004] The application aims to provide a power equipment inspection management system, which solves the technical problem that in the prior art, when a component fault is detected, other potential fault components cannot be quickly associated and judged, and accurate maintenance cannot be achieved.

[0005] A power equipment inspection management system, the inspection management system comprises an inspection set group for inspection, and further comprises:

[0006] A data acquisition module acquires target information of a power equipment to be detected, and the target information at least comprises historical fault data;

[0007] A region determination module determines a to-be-detected region based on the historical fault data of the power equipment to be detected, and synchronously determines each inspection point in the to-be-detected region and an inspection component corresponding to each inspection point, and the to-be-detected region comprises a high-fault region and a low-fault region;

[0008] An inspection classification module divides the inspection set group into two types, and respectively inspects the inspection components corresponding to each inspection point in the to-be-detected region according to a preset track;

[0009] A control module, when each inspection point corresponding to the inspection components in different to-be-detected regions is inspected by different types of inspection set groups, if a fault occurs in a certain component, whether there is an associated inspection component is judged according to a preset inspection component association library, if there is no associated component, the inspection set group continues to normally inspect a next inspection point; if there is an associated component, a suitable detection scheme is selected according to a preset detection strategy for re-inspection.

[0010] As a further scheme of the present application, the inspection classification module divides the inspection set group into first-type inspection devices and second-type inspection devices, the first-type inspection devices are used for inspecting high-fault areas, and the second-type inspection devices are used for inspecting low-fault areas.

[0011] As a further scheme of the present application, when a fault is found in a high-fault area by the first-type inspection device, if it is determined according to the preset inspection component association library that there is a component in the high-fault area associated with the current fault component, the first-type inspection device should immediately re-inspect these associated components, if it is determined according to the preset inspection component association library that there is a component in the low-fault area associated with the current fault component, the first-type inspection device transmits fault information and a list of associated components to the second-type inspection device, and the second-type inspection device re-inspects the associated components in the low-fault area;

[0012] When a fault is found in a low-fault area by the second-type inspection device, if it is determined according to the preset inspection component association library that there is a component in the high-fault area associated with the current fault component, the second-type inspection device should transmit fault information and a list of associated components to the first-type inspection device, and the first-type inspection device re-inspects the associated components in the high-fault area, if it is determined according to the preset inspection component association library that there is a component in the low-fault area associated with the current fault component, the second-type inspection device should re-inspect the associated components if the power of the second-type inspection device allows.

[0013] As a further scheme of the present application, the control module further comprises an associated component re-inspection judgment unit, when the first-type inspection device detects that the current component has no problem, whether to re-inspect the components associated with the current component is judged according to the following steps:

[0014] S1, obtaining historical fault data, current running state data, association characteristic data with the current component of the components associated with the current component, and current state data of the first-type inspection device;

[0015] S2, calculating a comprehensive risk assessment value of the components associated with the current component according to the historical fault frequency, fault severity, abnormal fluctuation of real-time running parameters, abnormal alarm signals, physical connection tightness and electrical parameter correlation between the components associated with the current component, and the detection accuracy, reliability, power condition of the first-type inspection device;

[0016] S3, judging whether the comprehensive risk assessment value of the components associated with the current component exceeds a preset re-inspection threshold, if yes, step S4 is executed, if no, step S5 is executed;

[0017] S4, determining to re-inspect the components associated with the current component, and assigning a re-inspection task to a suitable first-type or second-type inspection device;

[0018] S5, determining whether there is another component associated with the current component that has not been re-inspected, if yes, executing step S6, if no, executing step S7;

[0019] S6, selecting the next component associated with the current component as the component to be determined, and returning to step S2;

[0020] S7, determining whether the first type of inspection device has remaining power and time to perform additional inspection tasks, if yes, executing step S8, if no, executing step S9;

[0021] S8, performing remote state monitoring on the components associated therewith, and dynamically adjusting the re-inspection priority of the components associated therewith according to the monitoring results, if subsequent monitoring finds that the components associated therewith have abnormal signs, returning to step S2 to re-determine whether re-inspection is needed;

[0022] S9, marking the components associated therewith as components to be re-inspected, and re-inspecting at a subsequent appropriate time or by the second type of inspection device.

[0023] As a further aspect of the application, the control module further comprises an inspection device parameter adjustment unit, which selects components associated with the current component for re-inspection when the first type of inspection device detects that the current component has no problems and the number of components associated therewith exceeds a predetermined threshold, according to the following steps:

[0024] A1, obtaining parameter adjustment amplitude data of all components associated with the current component, and the current power state and parameter adjustment state of the first type of inspection device;

[0025] A2, determining whether the power of the first type of inspection device is lower than a predetermined low power threshold, if yes, executing step A3, otherwise executing step A4;

[0026] A3, randomly selecting an undetected component from all associated components as a component to be detected, and detecting the component; after detection is completed, determining whether the number of detected associated components reaches a predetermined threshold, if yes, ending the detection process, if no, returning to step A3;

[0027] A4, obtaining the target parameter of the current first type of inspection device, and determining whether the target parameter of the first type of inspection device is in an initial state, if yes, executing step A5, otherwise executing step A6, wherein the target parameter includes but is not limited to one or more of camera sharpness, current, and voltage;

[0028] A5, selecting the component with the smallest parameter adjustment amplitude from all undetected associated components as the component to be detected, and detecting the component; after detection is completed, removing the component from the list of components to be detected, and returning to step A5;

[0029] A6, adjust the parameters of the first type of inspection equipment to the ideal state to reduce the adjustment demand of subsequent detection, then select the parameter adjustment range maximum from all undetected associated components as the component to be detected, and detect the component; after detection, judge whether the component has a fault, if yes, end the detection process, if not, remove the component from the list of components to be detected, and return to step A6.

[0030] As a further scheme of the application, the adjustment of the parameters of the first type of inspection equipment to the ideal state specifically comprises:

[0031] When the power of the detection equipment is sufficient, the related parameters of the detection equipment are adjusted to a high-precision mode to obtain more accurate detection data;

[0032] When the power of the detection equipment is lower than a preset threshold, the related parameters of the detection equipment are adjusted to a low-precision mode to reduce power consumption.

[0033] As a further scheme of the application, during the execution of step A3, if a faulty component is detected, the information of the faulty component is recorded, and the following steps are executed:

[0034] B1, select a component with the smallest parameter adjustment range from the remaining undetected associated components as the component to be detected, and detect the component;

[0035] B2, after detection, judge whether the parameter adjustment range of the component is greater than a preset adjustment range threshold, if yes, end the detection process; if not, remove the component from the list of components to be detected, and return to step B1.

[0036] As a further scheme of the application, during the execution of step A5, if a faulty component is detected, the information of the faulty component is recorded, and the following steps are executed:

[0037] C1, randomly select a component from the remaining undetected associated components as the component to be detected, and detect the component;

[0038] C2, after detection, judge whether the number of detected associated components reaches a preset threshold, if yes, end the detection process; if not, return to step C1.

[0039] As a further scheme of the application, it further comprises:

[0040] B3, adjust the parameter adjustment range threshold of subsequent detection according to the type and fault degree of the faulty component;

[0041] B4, if the faulty component belongs to a key component or has a high fault degree, the threshold of the parameter adjustment range is reduced, and components with smaller parameter adjustment ranges are preferentially detected.

[0042] B5, if the fault component belongs to a non-critical component and the fault degree is low, appropriately increase the threshold of parameter adjustment range to speed up the detection process.

[0043] As a further aspect of the application, it further comprises:

[0044] C3, record the location and fault information of the fault component, and generate a detailed fault report;

[0045] According to the fault report, adjust the random selection strategy of technical solution 1, increase the selection probability of the adjacent or related components of the fault component;

[0046] C4, according to the fault report, adjust the random selection strategy, increase the selection probability of the adjacent or related components of the fault component;

[0047] C5, if multiple fault components are continuously detected, expand the range of random selection and increase the coverage probability of undetected components.

[0048] Compared with the prior art, the beneficial effects of the present application are:

[0049] The present application, by classification detection and correlation detection, helps to solve the problems of low efficiency, high risk of missed detection, difficult fault correlation judgment and other problems in traditional power distribution cabinet inspection, and by means of historical data, the inspection area and route are accurately planned, which helps to improve the inspection efficiency and reduce the labor and time cost; through the differentiated inspection strategy, the high-fault area is detected, and the hidden danger of missed detection is reduced; the intelligent fault correlation judgment and re-inspection mechanism can quickly locate the fault and potential risk components, realize accurate maintenance, and ensure the stable operation of the power distribution cabinet, providing a solid guarantee for the safe and reliable power supply of the power system. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 The present application is a system framework structure diagram. DETAILED DESCRIPTION

[0051] The technical solutions of the present application will be described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0052] Please refer to Figure 1 The present application provides a power equipment inspection management system, which comprises an inspection set for inspection, and further comprises:

[0053] a data acquisition module, configured to acquire target information of the power equipment to be detected, the target information at least including historical fault data;

[0054] a region determination module, configured to determine a to-be-detected region based on the historical fault data of the power equipment to be detected, and simultaneously determine each inspection point in the to-be-detected region and an inspection component corresponding to each inspection point, the to-be-detected region including a high-fault region and a low-fault region;

[0055] an inspection classification module, configured to divide the inspection set group into two categories, and perform inspection on the inspection components corresponding to each inspection point in the to-be-detected region according to a preset track respectively;

[0056] a control module, configured to, when the different types of inspection set groups perform inspection on the inspection components corresponding to each inspection point in different to-be-detected regions respectively, if it is detected that a certain component fails, determine whether there is an associated inspection component according to a preset inspection component association library, if there is no associated component, the inspection set group continues to normally inspect a next inspection point, and if there is an associated component, a suitable detection scheme is selected according to a preset detection strategy to perform re-inspection.

[0057] The data acquisition module acquires data in real time through various sensors (such as current sensors and temperature sensors) deployed on the power distribution cabinet, and at the same time, retrieves historical fault data from a power system historical database to construct an information file of the power distribution cabinet.

[0058] Further, the data acquisition module is specially responsible for collecting target information of the power equipment to be detected, i.e., the power distribution cabinet. The target information covers multiple key dimensions, wherein the historical fault data records detailed information such as the time of fault occurrence, the fault type (such as short circuit, overheating, insulation damage, etc.), and the specific position of fault during the past operation of the power distribution cabinet. In addition, the target information also includes real-time operation parameters (such as current, voltage, power, etc.) of the power distribution cabinet, equipment model specifications, installation time, etc.

[0059] The region determination module divides the power distribution cabinet into regions based on the historical fault data provided by the data acquisition module, and uses data analysis algorithms (such as clustering analysis and frequency statistics) to determine the to-be-detected region. The high-fault region refers to the parts that frequently fail historically, and these regions often have problems such as component aging, design defects, or poor operating environment. The low-fault region is a region with a relatively low probability of failure. While dividing the regions, the inspection points in each to-be-detected region are also determined. The inspection point is a detection position set for the key parts of the power distribution cabinet, and each inspection point corresponds to a specific inspection component, such as a circuit breaker, a fuse, a copper bar, etc.

[0060] The preset track is a scientific and planned inspection route according to the structural layout and functional characteristics of the power distribution cabinet, which can cover all inspection points.

[0061] Further, the inspection classification module divides the inspection set group (i.e. equipment for power distribution cabinet inspection) into two categories, and each category of inspection set group implements different inspection strategies. The first category of inspection set group is equipped with high-precision detection instruments (such as loop resistance tester, insulation resistance tester), mainly for high-fault areas and abnormal parts found by preliminary detection, for in-depth detection; the second category of inspection set group is equipped with rapid detection equipment (such as infrared thermal imager, portable partial discharge detector), focusing on rapid scanning to quickly identify obvious abnormal heating, discharge and other problems;

[0062] Among them, the inspection component association library is a database that records the functional association and electrical connection relationship between each component of the power distribution cabinet. To build a database that records the association relationship of each component of the power distribution cabinet, first collect static data such as equipment parameters, and at the same time, summarize historical fault records and other data, and use graph database technology to build a knowledge graph that can accurately reflect the component association state;

[0063] When different types of inspection set groups detect the inspection components, when a component is found to have a fault, the control module determines whether there are other components associated with the faulty component according to the pre-set inspection component association library. If there are no associated components, the control module will instruct the inspection set group to continue to inspect the next inspection point according to the plan; if there are associated components, the most suitable detection scheme is selected for re-inspection according to the pre-set detection strategy, so that through classification detection and association detection, it helps to solve the problems of low efficiency, high risk of missed detection, and difficulty in fault association judgment in traditional power distribution cabinet inspection. Through differentiated inspection strategies, high-fault areas are detected, reducing the risk of missed detection; the fault association judgment and re-inspection mechanism can quickly locate the fault and potential risk components, realize accurate maintenance, and ensure the stable operation of the power distribution cabinet, providing a solid guarantee for the safe and reliable power supply of the power system.

[0064] As an optional embodiment, the inspection classification module divides the inspection set group into first type inspection equipment and second type inspection equipment, the first type inspection equipment is used for inspecting high-fault areas, and the second type inspection equipment is used for inspecting low-fault areas.

[0065] Among the many inspection equipment, the first type inspection equipment and the second type inspection equipment cover multiple types, which include inspection drones, inspection robots and other key equipment. These two types of inspection equipment have many differences;

[0066] For example, in an inspection set group, the inspection drone has large battery capacity and high detection accuracy, so it has enough capacity to perform complex inspection tasks;

[0067] The second type of inspection drone has relatively low accuracy and limited power, and it is more suitable for performing simple inspection tasks;

[0068] It should be understood that, according to the operation characteristics and fault distribution law of the power distribution cabinet, the inspection set group is divided into two different function positioning device combinations, i.e. the first type of inspection device and the second type of inspection device, and different inspection strategies are implemented according to the different characteristics of the high and low fault areas of the power distribution cabinet, which is beneficial to solve the problems of unreasonable resource allocation, low efficiency, and not careful investigation of high-risk areas in the traditional inspection mode. Not only the discovery ability of hidden dangers in high-fault areas is improved, and the probability of failure is reduced, but also the inspection method of low-fault areas is optimized, unnecessary resource waste is reduced, the overall efficiency of power distribution cabinet inspection is significantly improved, and the stable operation of the power system is ensured.

[0069] As an optional embodiment, when a fault is found in the high-fault area by the first type of inspection device, if it is determined according to the preset inspection component association library that there is a component in the high-fault area associated with the current fault component, the first type of inspection device should immediately recheck these associated components. If it is determined according to the preset inspection component association library that there is a component in the low-fault area associated with the current fault component, the first type of inspection device will pass the fault information and the list of associated components to the second type of inspection device, and the second type of inspection device will recheck the associated components in the low-fault area.

[0070] When a fault is found in the low-fault area by the second type of inspection device, if it is determined according to the preset inspection component association library that there is a component in the high-fault area associated with the current fault component, the second type of inspection device should pass the fault information and the list of associated components to the first type of inspection device, and the first type of inspection device should recheck the associated components in the high-fault area. If it is determined according to the preset inspection component association library that there is a component in the low-fault area associated with the current fault component, the second type of inspection device should recheck the associated components if the power of the second type of inspection device allows.

[0071] Specifically, in the traditional inspection process of the power distribution cabinet, once a component failure is found, it is often difficult to quickly determine whether the failure will cause associated components to malfunction, resulting in low efficiency of fault troubleshooting. Either the potential hidden danger is not discovered due to the failure to timely check the associated components, ultimately leading to more serious failure, or the same fault handling method is used for different fault risk areas (high and low fault areas), without considering the regional characteristics and device configuration advantages, further exacerbating the inefficiency of fault handling.

[0072] When the first type of inspection device performs an inspection task in a high-fault area, if a fault is detected in a component, the device immediately calls a preset inspection component association library. If the association library determines that there is a component associated with the current faulty component and also in the high-fault area, since the first type of inspection device is equipped with high-precision detection instruments and is suitable for in-depth detection of complex faults and high-risk areas, the first type of inspection device will immediately re-inspect these associated components;

[0073] If the association library determines that there is a component associated with the current faulty component but in a low-fault area, the first type of inspection device will transfer the fault information and the list of associated components to the second type of inspection device. The second type of inspection device is responsible for low-fault area inspection and is more suitable for rapid screening. It will re-inspect the associated components in the low-fault area, ensuring inspection efficiency and reasonable allocation of resources;

[0074] When the second type of inspection device finds a fault in a low-fault area, it will also make a judgment based on the preset inspection component association library. If it determines that there is a component associated with the current faulty component and located in a high-fault area, since the high-fault area requires more professional and detailed detection, the second type of inspection device will transfer the fault information and the list of associated components to the first type of inspection device, which will use its high-precision detection capabilities to re-inspect the associated components in the high-fault area;

[0075] If the association library determines that there is a component associated with the current faulty component and also in a low-fault area, the second type of inspection device will re-inspect the associated components if its power allows. This is because the second type of inspection device inspects in a low-fault area. If it has sufficient power, it can directly re-inspect the associated components to reduce the time cost of information transmission and device mobilization, and quickly complete fault troubleshooting. If the power is insufficient, it will prioritize completing the current inspection task and then arrange detection of the associated components, thereby helping to solve the problems of low efficiency and resource waste in traditional fault-associated component troubleshooting. Based on the characteristics of high and low fault areas and the functional differences between the two types of inspection devices, the fault re-inspection tasks are reasonably allocated, ensuring deep detection of high-risk components while considering inspection efficiency and resource utilization, significantly improving the accuracy and timeliness of power distribution cabinet fault troubleshooting, reducing the risk of power system accidents caused by faults, and providing a strong guarantee for the stable operation of power distribution cabinets.

[0076] As an optional embodiment, the control module further includes an associated component re-inspection judgment unit that, when the first type of inspection device detects that the current component has no problems, judges whether to re-inspect the components associated with it according to the following steps:

[0077] S1, obtain the historical fault data, current operating state data, association characteristic data with the current component, and current state data of the first type of inspection device of the components associated with it;

[0078] S2, calculate a comprehensive risk assessment value of the component associated therewith according to the historical failure frequency, failure severity, abnormal fluctuation of real-time operation parameters, abnormal alarm signals, physical connection tightness and electrical parameter relevance with the current component, and the detection accuracy, reliability, and power situation of the first type of inspection device;

[0079] S3, determine whether the comprehensive risk assessment value of the component associated therewith exceeds a preset re-inspection threshold, if yes, execute step S4, if no, execute step S5;

[0080] S4, determine to re-inspect the component associated therewith, and assign the re-inspection task to a suitable first type or second type of detection device;

[0081] S5, determine whether there is another component associated with the current component that has not been determined for re-inspection, if yes, execute step S6, if no, execute step S7;

[0082] S6, select the next component associated with the current component as the component to be determined, and return to step S2;

[0083] S7, determine whether the first type of inspection device has remaining power and time to perform additional inspection tasks, if yes, execute step S8, if no, execute step S9;

[0084] S8, perform remote state monitoring on the component associated therewith, and dynamically adjust the re-inspection priority of the component associated therewith according to the monitoring result, if subsequent monitoring finds that the component associated therewith has abnormal signs, return to step S2 to re-determine whether re-inspection is needed;

[0085] S9, mark the component associated therewith as a component to be re-inspected, and re-inspect it at a suitable later opportunity or by a second type of detection device.

[0086] Specifically, during the inspection of the power distribution cabinet, when the first type of inspection device detects that the current component is normal, the traditional inspection mode usually ignores the components associated therewith, which may cause potential fault risks to be missed. Because even if the current component is normal, the associated components may still have fault risks due to historical failure risks, real-time operation abnormalities, or close association with the current component. On the other hand, if all associated components are indiscriminately re-inspected, it will cause waste of inspection resources and reduce the inspection efficiency;

[0087] Therefore, through the association component re-inspection judgment unit, it is possible to collect multi-dimensional data of all components associated with the current component under the condition that the current component detection is normal, including historical failure data (such as failure frequency, severity), current operating state data (such as temperature, current, voltage, and other real-time parameters), associated characteristic data (such as physical connection tightness, electrical parameter correlation), and the current state of the first type of inspection equipment (such as detection accuracy, reliability, remaining power), which constitutes the basis for risk assessment;

[0088] Further, based on the obtained data, the unit quantifies the risk from multiple dimensions, for example:

[0089] Historical dimension: analyze the historical failure frequency and failure severity of the associated components, and the components with high failure frequency or serious consequences are at higher risk;

[0090] Real-time state dimension: monitor abnormal fluctuations in real-time operating parameters and abnormal alarm signals, such as sudden temperature rise, unstable current, etc.;

[0091] Associated characteristic dimension: evaluate the physical connection tightness (such as hard connection vs. soft connection) and electrical parameter correlation (such as voltage dependence, current conduction path) with the current component;

[0092] Device capability dimension: consider the detection accuracy, reliability, and remaining power of the first type of inspection equipment to ensure that the evaluation results meet the actual detection capability, and generate a comprehensive risk assessment value for each associated component through weighted calculation;

[0093] Compare the comprehensive risk assessment value with the preset re-inspection threshold. The threshold is a risk threshold set based on historical failure data and expert experience, used to distinguish between high-risk components that need immediate re-inspection and low-risk components that can be temporarily handled;

[0094] If the evaluation value exceeds the threshold, the re-inspection task is assigned to the most suitable detection equipment according to the region (high / low failure region) and device characteristics of the associated components. For example, the associated components in the high failure region are preferentially assigned to the first type of inspection equipment, and the low failure region can be executed by the second type of detection equipment for re-inspection;

[0095] If the evaluation value does not exceed the threshold, it will be checked whether there are un-evaluated associated components. If there are, the next associated component will be evaluated; if all associated components have been evaluated, it will further judge whether the first type of inspection equipment has remaining resources (power and time) for additional inspection;

[0096] If the device resources are sufficient, remote state monitoring (such as real-time data collection through IoT sensors) will be performed on the associated components, and the re-inspection priority will be dynamically adjusted according to the monitoring results. Once abnormal signs are found, it will immediately re-evaluate whether re-inspection is needed;

[0097] If the device resources are insufficient, the associated components will be marked as pending re-inspection components, and will be arranged for re-inspection by a suitable device (such as a second type of detection device) in the subsequent inspection, to ensure that all potential risk components can be checked, thereby avoiding the problem of directly ignoring the potential risk of associated components due to the normality of the current component, thereby being able to identify the components that really need to be re-inspected, and helping to eliminate the inefficient practice of indiscriminately re-inspecting all associated components;

[0098] And by analyzing historical failures, real-time parameters and component association characteristics, high-risk components can be accurately located, and potential failures can be warned in advance; at the same time, tasks are intelligently allocated according to device capabilities, resource utilization is optimized, and the inspection cycle is shortened; when a failure is detected, the failure propagation can be quickly blocked and the impact range can be reduced.

[0099] It should be noted that in the power distribution cabinet inspection management system, the first type of inspection device is selected instead of the second type of detection device to perform part of the re-inspection task, which is based on the comprehensive consideration of device characteristics, failure area demand and resource optimization. Because the first type of device is equipped with high-precision instruments (such as loop resistance testers), which are good at detecting subtle faults in depth; while the second type of device mainly uses portable tools (such as ordinary infrared thermometers), which focuses on rapid screening. The risk of associated components in high-failure areas is complex and hidden, and requires the precise detection capability of the first type of device; assigning such tasks to the first type of inspection device can avoid resource waste due to the insufficient capacity of the second type of inspection device.

[0100] As an optional embodiment, the control module further comprises an inspection device parameter adjustment unit, which selects the components associated with the current component for re-inspection according to the following steps when the first type of inspection device detects that the current component has no problem and the number of components associated with it exceeds a preset threshold:

[0101] A1, obtain the parameter adjustment amplitude data of all components associated with the current component, and the current power state and parameter adjustment state of the first type of inspection device;

[0102] A2, determine whether the power of the first type of inspection device is lower than a preset low power threshold, if yes, execute step A3, otherwise execute step A4;

[0103] A3, randomly select an undetected component from all associated components as a to-be-detected component, and detect the component; after the detection is completed, determine whether the number of detected associated components reaches a preset threshold, if yes, end the detection process, if no, return to step A3;

[0104] A4, obtain the target parameter of the current first type of inspection equipment, and determine whether the target parameter of the first type of inspection equipment is in an initial state, if yes, execute step A5, otherwise execute step A6, wherein the target parameter includes but is not limited to one or more of camera sharpness, current and voltage;

[0105] A5, select a component with the smallest parameter adjustment range from all undetected associated components as a to-be-detected component, and detect the component; after detection is completed, remove the component from the to-be-detected component list, and return to step A5;

[0106] A6, adjust the parameters of the first type of inspection equipment to an ideal state to reduce the adjustment requirement of subsequent detection, then select a component with the largest parameter adjustment range from all undetected associated components as a to-be-detected component, and detect the component; after detection is completed, determine whether the component has a fault, if yes, end the detection process, if not, remove the component from the to-be-detected component list, and return to step A6.

[0107] Specifically, in the process of power distribution cabinet inspection, when the first type of inspection equipment faces a large number of associated components, the traditional disordered detection method is easy to cause waste of equipment resources, low detection efficiency, and even unable to complete the detection of key components due to insufficient power. If all associated components are detected at will, on the one hand, the detection equipment will frequently adjust the parameters, which shortens the service life of the equipment; on the other hand, when the power of the equipment is limited, the truly important components to be checked may be missed due to blind detection;

[0108] Therefore, first, the parameter adjustment range data of all components associated with the current component is obtained, which reflects the degree of adjustment of the parameters (such as camera sharpness, current detection range) of the first type of inspection equipment when detecting different components. At the same time, the current power state and parameter adjustment state of the first type of inspection equipment are obtained;

[0109] Then, it is determined whether the power of the first type of inspection equipment is lower than a preset low power threshold. The threshold is set according to the average power consumption of the equipment and the power required to complete the regular detection task, etc.

[0110] When the power of the equipment is lower than the preset low power threshold, in order to avoid interruption of detection due to power consumption, an undetected component is randomly selected from all associated components as a to-be-detected component, and is detected. After detection is completed, it is determined whether the number of detected associated components reaches a preset threshold, which is a reasonable detection number set according to experience or the importance of the power distribution cabinet. If the threshold is reached, the detection process is ended; if not, the next undetected component is randomly selected for detection, which is conducive to completing a certain number of detection tasks before the power is consumed as much as possible;

[0111] If the equipment has sufficient power, the target parameters of the current first type of inspection equipment are obtained, and the target parameters include one or more of key parameters such as camera sharpness, current, and voltage that affect the detection effect. Then, it is determined whether the target parameters of the first type of inspection equipment are in an initial state, i.e., a state in which the equipment has not adjusted the related parameters for previous detection tasks.

[0112] When the target parameters are in the initial state, to reduce the number of equipment parameter adjustments and reduce equipment loss, the component with the smallest parameter adjustment range from all undetected associated components is selected as the to-be-detected component for detection. After detection is completed, the component is removed from the to-be-detected component list, and then the next undetected component with the smallest parameter adjustment range is selected until all necessary detections are completed, thereby achieving the efficiency of the detection process and the low-loss operation of the equipment.

[0113] If the target parameters are not in the initial state, it indicates that the equipment has been adjusted. At this time, the parameters of the first type of inspection equipment are adjusted to an ideal state, which is a device parameter setting that minimizes the subsequent detection parameter adjustment demand after considering the detection needs of all associated components. After adjustment, the component with the largest parameter adjustment range from all undetected associated components is selected as the to-be-detected component for detection. Because the component with the largest parameter adjustment range is detected first, the equipment parameters can be adjusted once, which helps to avoid frequent small adjustments of parameters for detecting other components. For example, if the current equipment parameters have been optimized for high-voltage detection scenarios, and there is a component that needs low-current precision detection in the associated components (with a large adjustment range), detecting this component directly can complete the detection after one parameter adjustment. Subsequent detection of other components may only require fine tuning or no adjustment. If the opposite detection strategy is used, detecting components with small adjustment ranges first may require switching between multiple small adjustments, increasing the total number of adjustments, wasting equipment, and prolonging detection time.

[0114] After detection is completed, it is determined whether the component has a fault. If there is a fault, the detection process is ended, and the fault is handled first. If there is no fault, the component is removed from the to-be-detected component list, and the next undetected component with the largest parameter adjustment range is selected for detection. This ensures that components with the largest differences in equipment parameter requirements are detected first when the equipment parameters have been adjusted, thereby effectively solving the problems of resource waste, low efficiency, and incomplete detection that may occur when the first type of inspection equipment faces a large number of associated components in power distribution cabinet inspection. In addition, when the equipment has insufficient power, a random detection strategy is used to ensure basic detection coverage. When the equipment has sufficient power, the detection components are intelligently selected based on the equipment parameter state, the number of parameter adjustments is reduced, and the detection efficiency is improved.

[0115] As an optional embodiment, adjusting the parameters of the first type of inspection equipment to the ideal state specifically includes:

[0116] When the detection device has sufficient power, the relevant parameters of the detection device are adjusted to a high-precision mode to obtain more accurate detection data.

[0117] When the detection device has power lower than a preset threshold, the relevant parameters of the detection device are adjusted to a low-precision mode to reduce power consumption.

[0118] The relevant parameters include but are not limited to the resolution of the camera, the sensitivity of the sensor, the accuracy of the measuring device, etc.

[0119] In the power distribution cabinet inspection, when the detection device has sufficient power, the relevant parameters of the detection device are adjusted to a high-precision mode. In the high-precision mode, the detection parameters of the detection device are optimized to obtain more accurate and detailed detection data. For example, for current detection, the high-precision mode can improve the resolution of current measurement, so as to detect smaller current changes and help find problems such as poor contact or slight overload in the circuit.

[0120] When the detection device has power lower than a preset threshold, the relevant parameters of the detection device are adjusted to a low-precision mode. The core goal of the low-precision mode is to reduce the power consumption of the device to ensure that the device can complete the necessary detection tasks. In the low-precision mode, the detection device appropriately reduces the accuracy requirements of some non-critical parameters, such as relaxing the resolution range of current measurement and reducing the image acquisition frequency of the infrared thermal imager. Although the data accuracy obtained in this mode is reduced, it still meets the basic fault detection requirements, which is conducive to ensuring that the device can still complete the detection work of the key parts in the case of limited power.

[0121] As an optional embodiment, in the process of executing step A3, if a faulty component is detected, the faulty component information is recorded, and the following steps are executed:

[0122] B1, selecting a component with the smallest parameter adjustment amplitude from the remaining undetected associated components as a to-be-detected component, and detecting the component;

[0123] B2, after the detection is completed, it is judged whether the parameter adjustment amplitude of the component is greater than a preset adjustment amplitude threshold, if yes, the detection process is ended, if not, the component is removed from the to-be-detected component list, and step B1 is returned.

[0124] Specifically, in the power distribution cabinet inspection, when the first type of inspection equipment is low in power and adopts a random detection strategy, if the faulty component is found and the random detection is still blindly continued, on the one hand, the subsequent detection may accelerate the consumption of power due to frequent adjustment of equipment parameters (such as detection range), leading to missed detection of key components; on the other hand, disordered detection is easy to cause repeated changes of equipment parameters, reduce detection accuracy, and affect accurate judgment of faults of the remaining associated components;

[0125] When the faulty component is detected, step B1 is immediately performed to screen a component with the smallest parameter adjustment amplitude from the remaining undetected associated components as a to-be-detected object. The parameter adjustment amplitude reflects the difficulty of adjusting the parameters (such as current detection range and infrared thermal imaging resolution) of the equipment when detecting different components. Taking current detection of the power distribution cabinet as an example, if the current equipment is set to detect a certain current interval, the associated component that is also applicable to the interval is preferentially selected for detection, which can avoid consumption of additional power due to frequent switching of the range. Thus, the number of times of adjusting the parameters of the equipment can be minimized, power consumption can be reduced, and detection errors caused by parameter adjustment can be reduced;

[0126] After the detection is completed, the system enters step B2 to compare and judge the parameter adjustment amplitude of the detected component with a preset adjustment amplitude threshold. The threshold is a key index set by comprehensively considering equipment performance, remaining power, and requirements for detection of the power distribution cabinet. If the parameter adjustment amplitude of the detected component is greater than the threshold, it means that detecting the next component will cause large changes in the parameters of the equipment, which will not only consume a large amount of power, but also may cause a decrease in detection accuracy due to parameter adjustment. At this time, the detection process should be ended immediately, and the discovered fault should be preferentially handled. If the parameter adjustment amplitude does not exceed the threshold, the component is removed from the to-be-detected list, and step B1 is returned to continuously select a component with the smallest parameter adjustment amplitude for detection, so as to complete more effective detection before the power is exhausted. Thus, it is beneficial to solve the detection contradiction of the first type of inspection equipment in the low-power fault scenario. By preferentially detecting the component with the smallest parameter adjustment amplitude, power consumption and accuracy interference caused by adjustment of the parameters of the equipment can be reduced, the effectiveness of detection can be maximized under the condition of limited power, the continuous investigation of the associated components of the power distribution cabinet can be ensured, missed detection of key components due to disordered detection can be avoided, the high-energy detection process can be terminated in time when the equipment resources are scarce, the discovered fault can be preferentially handled, the efficient balance between fault handling and remaining detection tasks is achieved, and the reliability and emergency handling capability of the power distribution cabinet inspection are effectively ensured.

[0127] As an optional embodiment, in the process of performing step A5, if a faulty component is detected, the information of the faulty component is recorded, and the following steps are performed:

[0128] C1, a component is randomly selected from the remaining undetected associated components as a to-be-detected component, and the component is detected;

[0129] C2, after the detection is completed, it is judged whether the number of detected associated components reaches a preset threshold, if yes, the detection process is ended, if no, step C1 is returned.

[0130] Specifically, in the power distribution cabinet inspection scene, when the first type of inspection equipment is in the initial state of the target parameter, and the detection is performed according to the “selecting the component with the smallest parameter adjustment range”, if a faulty component is detected, the original strategy may be limited. Because the faulty component with a small parameter adjustment range may not be highly related to the discovered faulty component in terms of fault association and potential risk. If the component with a small parameter adjustment range is continuously selected for detection, a high-risk component that is closely related to the current fault but has a large parameter adjustment range may be missed, resulting in that the fault hidden danger cannot be timely and comprehensively investigated;

[0131] Therefore, after the faulty component is detected during the execution of step A5, the system enters step C1, and a component is randomly selected from the remaining undetected associated components as a to-be-detected component. By using the random selection method, the limitation of selecting the component only according to the parameter adjustment range is broken. In the complex electrical connection relationship of the power distribution cabinet, random selection can more widely cover different types and different risk levels of associated components, which is beneficial to avoid the detection blind spot caused by the inherent selection logic. For example, when a certain circuit breaker is detected to be faulty, the random selection may select a fuse or a relay that is closely connected to the circuit breaker in terms of electrical connection but has a large parameter adjustment range, which is helpful to quickly discover the potential cascading failure risk;

[0132] After the detection of the randomly selected component is completed, the system performs step C2 to judge whether the number of detected associated components reaches a preset threshold. The preset threshold is set according to the size, complexity and historical fault data of the power distribution cabinet and other comprehensive factors. If the number of detected components reaches the threshold, it means that under the current conditions, a sufficient number of associated components have been detected, and the fault influence range can be evaluated more comprehensively, and the detection process is ended at this time. If the threshold is not reached, step C1 is returned, and the next undetected component is randomly selected for detection, to ensure that the associated components are fully investigated and other hidden dangers related to the current fault are discovered as much as possible; thereby, the problem of incomplete fault investigation caused by single detection logic under certain detection conditions is solved. When the faulty component is detected, the to-be-detected component is randomly selected, which breaks through the limitation of the original parameter adjustment range selection, and helps to improve the detection coverage of the complex associated components of the power distribution cabinet, especially in the scene where the associated hidden dangers need to be quickly and comprehensively investigated after the fault occurs.

[0133] As an optional embodiment, it further includes:

[0134] B3, adjusting the parameter adjustment range threshold of subsequent detection according to the type and fault degree of the faulty component;

[0135] B4, if the faulty component belongs to a critical component or has a high degree of failure, reduce the threshold of the parameter adjustment range, and preferentially detect components with smaller parameter adjustment ranges;

[0136] B5, if the faulty component belongs to a non-critical component and has a low degree of failure, appropriately increase the threshold of the parameter adjustment range to speed up the detection process.

[0137] It should be understood that in the power distribution cabinet inspection, the existing parameter adjustment range threshold setting method is relatively fixed and difficult to adapt to complex and variable fault scenarios.

[0138] Therefore, after detecting the faulty component, the parameter adjustment range threshold for subsequent detection is adjusted according to the type and degree of failure of the faulty component. The type of faulty component covers circuit breakers, fuses, relays and other key components of the power distribution cabinet, and the degree of failure is evaluated by multiple indicators such as the severity of the fault (such as whether it causes local power outage, whether there is a fire hazard, etc.), repair difficulty, etc. Thus, the subsequent detection strategy can be flexibly adapted to the actual fault situation;

[0139] If the faulty component belongs to a critical component or has a high degree of failure, for example, the main circuit breaker of the power distribution cabinet has a short circuit fault, which may directly affect the operation of the entire power distribution system. At this time, step B4 is executed to reduce the threshold of the parameter adjustment range. This means that in subsequent detection, components with smaller parameter adjustment ranges will be preferentially selected for detection. Because components with smaller parameter adjustment ranges are easier to detect under the current device parameter state, they can complete the troubleshooting faster, avoid wasting time and power by frequently adjusting device parameters, ensure that other potential risk points associated with critical fault components are found in the shortest time, and prevent the fault from further spreading;

[0140] When the faulty component belongs to a non-critical component and has a low degree of failure, such as a damaged indicator light in the power distribution cabinet, which has a small impact on the operation of the power system. The system executes step B5: appropriately increases the threshold of the parameter adjustment range. This adjustment allows more components with slightly larger parameter adjustment ranges to be selected in subsequent detection, reducing the strict restriction on "minimum adjustment range". In this way, while ensuring the effectiveness of detection, unnecessary low-priority detection can be skipped, the detection process is accelerated, and limited resources are concentrated on more important components, improving overall inspection efficiency.

[0141] As an optional embodiment, it also includes:

[0142] C3, record the location and failure information of the faulty component, and generate a detailed failure report;

[0143] According to the failure report, adjust the random selection strategy of technical solution 1 to increase the selection probability of components adjacent or related to the faulty component;

[0144] C4. Adjust the random selection strategy based on the fault report, increasing the probability of selecting components adjacent or related to the faulty component.

[0145] C5. If multiple faulty components are continuously detected, expand the range of random selection, increasing the coverage probability of undetected components.

[0146] It should be understood that in the power distribution cabinet inspection, there are two major problems with the traditional random detection strategy: one is that it is difficult to target the associated risks after fault location, and the other is that the detection range is limited in the continuous fault scenario, leading to an increased rate of missed detection. When a faulty component is detected, if only the information is recorded without adjusting the strategy, potential risks of adjacent or electrically related components may be missed. If multiple faults are continuously found, the original random range is maintained, which may lead the system into an inefficient cycle of repeated detection of high-risk areas.

[0147] By recording the precise location of the faulty component (such as the power distribution cabinet number, loop level) and detailed fault information (such as short circuit type, temperature anomaly value), a structured fault report is generated. Based on this report, the random selection strategy is dynamically adjusted: by analyzing the physical layout and electrical connection of the faulty component, higher selection weights are given to adjacent or functionally related components.

[0148] By constructing a fault propagation probability model, the possibility of each component being affected by the fault is calculated based on historical fault data and power system topology. For example, other devices on the same bus as the faulty circuit breaker, branch components sharing the power source, etc., will be assigned a higher selection probability.

[0149] When multiple faulty components are continuously detected, an adaptive range expansion mechanism is triggered. By analyzing the fault distribution pattern, if it is found that the faults are concentrated in a certain area, the system will expand the random selection range, increasing the coverage of the edge area or previously undetected components.

[0150] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A power equipment inspection and management system, characterized in that, The inspection management system comprises an inspection set group for inspection, and further comprises: a data acquisition module, which acquires target information of the power equipment to be detected, the target information at least comprising historical fault data; a region determination module, which determines a to-be-detected region based on the historical fault data of the power equipment to be detected, and synchronously determines each inspection point in the to-be-detected region and the inspection components corresponding to each inspection point, the to-be-detected region comprising a high-fault region and a low-fault region; an inspection classification module, which divides the inspection set group into two types, and respectively inspects the inspection components corresponding to each inspection point in the to-be-detected region according to a preset trajectory; a control module, which, when the inspection set group of different types inspects the inspection components corresponding to each inspection point in different to-be-detected regions, if a fault is detected in a certain component, determines whether there is an associated inspection component according to a preset inspection component association library, if there is no associated component, the inspection set group continues to normally inspect the next inspection point; if there is an associated component, a suitable detection scheme is selected according to a preset detection strategy to perform re-inspection; the control module further comprises an associated component re-inspection judgment unit, which, when the first type of inspection equipment detects that the current component has no problem, judges whether to perform re-inspection on the associated component according to the following steps: S1, acquiring the historical fault data, current operating state data, association characteristic data with the current component, and current state data of the first type of inspection equipment of the associated component; S2, calculating the comprehensive risk assessment value of the associated component according to the historical fault frequency, fault severity, abnormal fluctuation of real-time operating parameters, abnormal alarm signal, physical connection tightness and electrical parameter correlation between the associated component and the current component, and the detection accuracy, reliability, and power situation of the first type of inspection equipment; S3, judging whether the comprehensive risk assessment value of the associated component exceeds a preset re-inspection threshold, if yes, performing step S4, if no, performing step S5; S4, determining to perform re-inspection on the associated component, and assigning the re-inspection task to a suitable first type or second type of detection equipment; S5, judging whether there is another component associated with the current component that has not been subjected to re-inspection judgment, if yes, performing step S6, if no, performing step S7; S6, selecting the next component associated with the current component as a to-be-judged component, and returning to step S2; S7, judging whether the first type of inspection equipment has remaining power and time to perform additional inspection tasks, if yes, performing step S8, if no, performing step S9; S8, performing remote state monitoring on the associated component, and dynamically adjusting the re-inspection priority of the associated component according to the monitoring result, if subsequent monitoring finds that the associated component has abnormal signs, returning to step S2 to re-judge whether re-inspection is needed; S9, marking the associated component as a to-be-re-inspected component, and performing re-inspection at a suitable subsequent opportunity or by the second type of detection equipment.

2. The power equipment inspection management system according to claim 1, wherein The inspection classification module divides the inspection set group into first type inspection equipment and second type inspection equipment, the first type inspection equipment is used for inspecting high failure area, and the second type inspection equipment is used for inspecting low failure area.

3. The power equipment inspection management system of claim 1, wherein, When a fault is found in the high failure area by the first type inspection equipment, if it is determined according to the preset inspection component association library that there is a component in the high failure area associated with the current fault component, the first type inspection equipment should immediately re-inspect these associated components, if it is determined according to the preset inspection component association library that there is a component in the low failure area associated with the current fault component, the first type inspection equipment will pass the fault information and the list of associated components to the second type inspection equipment, and the second type inspection equipment will re-inspect the associated components in the low failure area; When a fault is found in the low failure area by the second type inspection equipment, if it is determined according to the preset inspection component association library that there is a component in the high failure area associated with the current fault component, the second type inspection equipment should pass the fault information and the list of associated components to the first type inspection equipment, and the first type inspection equipment will re-inspect the associated components in the high failure area, if it is determined according to the preset inspection component association library that there is a component in the low failure area associated with the current fault component, the second type inspection equipment should re-inspect the associated components as long as the power of the second type inspection equipment allows.

4. The power equipment inspection management system of claim 1, wherein, The control module further comprises an inspection equipment parameter adjustment unit, when the first type inspection equipment detects that the current component has no problem and the number of components associated with the current component exceeds a preset threshold, the following steps are selected to re-inspect the components associated with the current component: A1, obtaining the parameter adjustment amplitude data of all components associated with the current component, and the current power state and parameter adjustment state of the first type inspection equipment; A2, determining whether the power of the first type inspection equipment is lower than a preset low power threshold, if yes, executing step A3, otherwise executing step A4; A3, randomly selecting an undetected component from all associated components as a to-be-detected component, and detecting the component; after the detection is completed, determining whether the number of detected associated components reaches a preset threshold, if yes, ending the detection process, if no, returning to step A3; A4, obtaining the target parameter of the current first type inspection equipment, and determining whether the target parameter of the first type inspection equipment is in an initial state, if yes, executing step A5, otherwise executing step A6, wherein the target parameter includes but is not limited to one or more of camera sharpness, current and voltage; A5, selecting a component with the smallest parameter adjustment amplitude from all undetected associated components as a to-be-detected component, and detecting the component; after the detection is completed, removing the component from the to-be-detected component list, and returning to step A5; A6, selecting a component with the largest parameter adjustment amplitude from all undetected associated components as a to-be-detected component, and detecting the component; after the detection is completed, removing the component from the to-be-detected component list, and returning to step A6. A6, adjust the parameters of the first type of inspection equipment to the ideal state to reduce the adjustment demand of subsequent detection, then select the component with the largest parameter adjustment range from all undetected associated components as the component to be detected, and detect the component; after detection, determine whether the component has a fault, if yes, end the detection process, if not, remove the component from the list of components to be detected, and return to step A6.

5. The power equipment inspection management system of claim 4, wherein, Adjusting the parameters of the first type of inspection equipment to the ideal state specifically includes: When the power of the detection equipment is sufficient, adjusting the relevant parameters of the detection equipment to the high-precision mode to obtain more accurate detection data; When the power of the detection equipment is lower than the preset threshold, adjusting the relevant parameters of the detection equipment to the low-precision mode to reduce power consumption.

6. The power equipment inspection management system of claim 4, wherein, During the execution of step A3, if a faulty component is detected, record the faulty component information, and perform the following steps: B1, select the component with the smallest parameter adjustment range from the remaining undetected associated components as the component to be detected, and detect the component; B2, after detection, determine whether the parameter adjustment range of the component is greater than the preset adjustment range threshold, if yes, end the detection process; If not, remove the component from the list of components to be detected, and return to step B1.

7. The power equipment inspection management system of claim 4, wherein, During the execution of step A5, if a faulty component is detected, record the faulty component information, and perform the following steps: C1, randomly select a component from the remaining undetected associated components as the component to be detected, and detect the component; C2, after detection, determine whether the number of detected associated components reaches the preset threshold, if yes, end the detection process; if not, return to step C1.

8. The power equipment inspection management system of claim 6, wherein, Further comprising: B3, adjusting the parameter adjustment range threshold of subsequent detection according to the type and fault degree of the faulty component; B4, if the faulty component is a critical component or has a high fault degree, reduce the threshold of the parameter adjustment range, and preferentially detect the component with a smaller parameter adjustment range; B5, if the faulty component is a non-critical component and has a low fault degree, appropriately increase the threshold of the parameter adjustment range to speed up the detection process.

9. The power equipment inspection management system of claim 7, wherein, Further comprising: C3, record the location and fault information of the faulty component, and generate a detailed fault report; According to the fault report, adjust the random selection strategy of technical solution 1 to increase the selection probability of adjacent or related components of the faulty component; C4, according to the fault report, adjust the random selection strategy to increase the selection probability of adjacent or related components of the faulty component; C5, if multiple faulty components are detected in succession, expand the range of random selection to increase the coverage probability of undetected components.

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