A method and system for inspection by a robot, a storage medium and an electronic device

Abstract

This application relates to an inspection robot inspection method, system, storage medium, and electronic device, belonging to the field of equipment inspection technology. The method includes: determining the inspection sequence of key inspection equipment based on the fault impact value of each key inspection equipment; determining multiple initial inspection paths based on the actual location, the equipment location of each key inspection equipment, and the inspection sequence; obtaining the actual wind direction of the target wind power station; selecting a target inspection path from the multiple initial inspection paths based on the actual wind direction; optimizing the target inspection path based on multiple second historical energy devices, the historical time period, and the alternative inspection devices to obtain a final inspection path; and controlling the target inspection robot to perform energy equipment inspection of the target wind power station according to the final inspection path. This application improves the inspection quality of inspection robots.

Description

Technical Field

[0001] This application relates to the field of equipment inspection technology, specifically to an inspection robot inspection method, system, storage medium, and electronic equipment. Background Technology

[0002] An inspection robot is an intelligent piece of equipment that uses a mobile robot as a carrier and is equipped with various sensing devices such as visible light cameras, infrared thermal imagers, sound sensors, and gas detectors. It can autonomously complete inspection tasks in specific areas. By integrating multi-source information such as machine vision, GPS, GIS, and electromagnetic fields, it achieves autonomous navigation and can replace manual labor in complex, dangerous, or highly repetitive environments. It is widely used in various fields, including energy equipment inspection in the energy and power industry (wind power plants). Specifically, energy equipment inspection refers to the use of robots with autonomous movement and intelligent sensing capabilities to automatically and intelligently check the operational status and collect data from energy equipment in the energy and power industry, replacing or assisting manual labor in completing high-risk, repetitive, and high-intensity inspection tasks.

[0003] Currently, the inspection method for energy equipment by inspection robots is usually as follows: based on fixed static data, such as the theoretical location of the energy equipment to be inspected and the terrain outline of the area where the energy equipment is located, the inspection path of the inspection robot is planned, and then the inspection is carried out according to the planned inspection path. However, the factors that affect the inspection robot during the inspection process are complex and changeable, and the inspection path planned by relying solely on static data is not very reasonable, resulting in poor inspection quality of the inspection robot. Summary of the Invention

[0004] To improve the inspection quality of inspection robots, this application provides an inspection robot inspection method, system, storage medium, and electronic device.

[0005] The first aspect of this application provides an inspection method for an inspection robot, specifically including: Obtain the actual location of the target inspection robot in the target wind power station, and obtain multiple first historical energy devices that have experienced failures in the target wind power station and the types of historical failures that have occurred in the first historical energy devices; Multiple energy devices to be inspected are identified from the multiple first historical energy devices, and the failure impact value of the energy devices to be inspected is determined according to the historical failure types of the energy devices to be inspected. The failure impact value characterizes the impact of the failure of the energy devices to be inspected on the overall operation of the target wind power station. If the fault impact value is greater than the preset impact value threshold, the energy equipment to be inspected is identified as a key inspection equipment. If the fault impact value is not greater than the impact value threshold, the energy equipment to be inspected is identified as a candidate inspection equipment. Based on the fault impact value of each key inspection equipment, the inspection sequence of the corresponding key inspection equipment is determined. Based on the actual location, the equipment location of each key inspection equipment, and the inspection sequence, multiple initial inspection paths are determined. The actual wind direction of the target wind power station is obtained. Based on the actual wind direction, a target inspection path is selected from the multiple initial inspection paths. Multiple second historical energy devices in the target wind power station that have caused electromagnetic interference to the inspection robot within a first preset distance and the historical time periods during which the second historical energy devices caused electromagnetic interference are obtained. The target inspection path is the initial inspection path that is least affected by wind resistance for the target inspection robot. Based on the multiple second historical energy devices, the historical time period, and the alternative inspection devices, the target inspection path is optimized to obtain the final inspection path, and the target inspection robot is controlled to perform energy equipment inspection on the target wind power station according to the final inspection path.

[0006] By employing the aforementioned technical solution, after obtaining the actual location of the target inspection robot, the first historical energy equipment, and the historical fault types, and combining this with the historical fault occurrences, energy equipment to be inspected is selected from multiple first historical energy equipment. Then, based on the historical fault types of the energy equipment to be inspected, the fault impact value is determined, thereby quantifying the magnitude of the impact of the fault on the target wind power station. If the fault impact value is greater than the impact value threshold, it indicates that the energy equipment to be inspected has malfunctioned and has a significant impact on the target wind power station, thus being identified as a key inspection equipment; otherwise, it is identified as a candidate inspection equipment. Furthermore, based on the fault impact value of key inspection equipment, the corresponding inspection sequence is determined. Then, combined with the actual position of the robot and the equipment positions of each key inspection equipment, multiple initial inspection paths are generated to ensure that the inspection work prioritizes the equipment with a high degree of fault impact, ensuring that the inspection focus is highlighted and improving the targeting of the inspection. Furthermore, combined with the actual wind direction of the target wind power station, the target inspection path with the least wind resistance is selected from multiple initial inspection paths, effectively reducing the impact of wind direction on the operational stability and energy consumption of the inspection robot. At the same time, the historical data of the second energy equipment in the target wind power station that has caused electromagnetic interference to the inspection robot within the first preset distance and the historical time period of the interference are collected. Combined with the alternative inspection equipment, the target inspection path is optimized to obtain the final inspection path. This not only avoids the impact of electromagnetic interference on the operational accuracy of the inspection robot and the accuracy of the inspection data, but also makes full use of the alternative inspection equipment resources to achieve comprehensive inspection coverage. Finally, the inspection robot is controlled to carry out inspection work according to the optimized final inspection path, making the inspection path planning more reasonable and accurate, thereby improving the inspection quality of the target inspection robot.

[0007] In one implementation, optimizing the target inspection path based on the plurality of second historical energy devices, the historical time period, and the alternative inspection devices to obtain the final inspection path specifically includes: Identify at least one device of concern from the plurality of second historical energy devices; Based on the historical periods during which the devices of concern cause electromagnetic interference to the inspection robot, at least one period of concern is identified. Calculate the device weight of the device to be monitored and calculate the time period weight of each time period to be monitored. The device weight represents the likelihood of the device to be monitored causing electromagnetic interference to the inspection robot, and the time period weight represents the likelihood of the device to be monitored causing interference to the inspection robot within the corresponding time period to be monitored. The first estimated time for the target inspection robot to reach the next inspection device is obtained. Based on the first estimated time, the device weight, the time period weight, and the alternative inspection devices, the target inspection path is optimized to obtain the final inspection path. The next inspection device is the next key inspection device that needs to be inspected at the actual position in the target inspection path.

[0008] In one implementation, optimizing the target inspection path based on the first estimated time, the equipment weight, the time period weight, and the candidate inspection equipment to obtain the final inspection path specifically includes: If the period of time corresponding to the device of concern includes the first estimated time, then the device of concern is determined as a reference device, and the period of time of concern including the first estimated time is determined as a reference period. The device weight of the reference device is multiplied by the time period weight of the reference time period to obtain the first risk coefficient of electromagnetic interference generated by the reference device. When the first risk coefficient is greater than the preset coefficient threshold, determine whether the next inspection device is the reference device; If the next inspection device is the reference device, then the current actual remaining power of the target inspection robot is obtained, and the target inspection path is optimized based on the actual remaining power and the alternative inspection devices to obtain the final inspection path.

[0009] In one implementation, optimizing the target inspection path based on the actual remaining power and the alternative inspection equipment to obtain the final inspection path specifically includes: When the actual remaining power is greater than a preset power threshold, a supplementary inspection device with the largest fault impact value is selected from at least one alternative inspection device within a second preset distance of the actual location, and a first sub-path is determined. The first sub-path and the second sub-path are combined to obtain the final inspection path. The first sub-path includes the path from the actual location to the supplementary inspection device and the path from the supplementary inspection device to the next inspection device. The second sub-path is the path in the target inspection path other than the path from the actual location to the next inspection device. When the actual remaining power is not greater than the preset power threshold, the current actual speed of the target inspection robot is reduced to obtain the target speed, and the target inspection path is determined as the final inspection path. The process of controlling the target inspection robot to perform energy equipment inspection on the target wind power station according to the final inspection path specifically includes: Based on the target speed, the target inspection robot is controlled to inspect the energy equipment of the target wind power station according to the final inspection path.

[0010] In one implementation, the step of reducing the current actual speed of the target inspection robot to obtain the target speed specifically includes: The current actual speed of the target inspection robot is reduced by a preset value to obtain an initial speed, and the distance from the actual position to the next inspection device is obtained; Divide the distance by the initial speed to obtain the estimated travel time of the target inspection robot, and obtain the second estimated time based on the current time and the estimated travel time; When the second estimated time is included in the time period of concern corresponding to the next inspection equipment, the time period of concern that includes the second estimated time is determined as an important time period; The equipment weight of the next inspection equipment is multiplied by the time period weight of the important time period to obtain the second risk coefficient of electromagnetic interference generated by the next inspection equipment. If the second risk coefficient is not greater than the preset coefficient threshold, then the initial speed is determined as the target speed; If the second estimated time is not included in the time period of concern corresponding to the next inspection equipment, the initial speed is determined as the target speed.

[0011] In one implementation, the step of reducing the current actual speed of the target inspection robot to obtain the target speed further includes: The equipment weight of the next inspection equipment is multiplied by the time period weight of each time period to be arrived, resulting in multiple multiplication results. The time period to be arrived is the time period to be monitored after the first estimated time. The minimum multiplication result is selected from all the multiplication results, and when the minimum multiplication result is not greater than a preset coefficient threshold, the time period to be arrived corresponding to the minimum multiplication result is determined as the appropriate time period to arrive. Select the maximum arrival time from the suitable arrival time periods, and subtract the current time from the maximum arrival time to obtain the suitable travel time of the target inspection robot; The distance from the actual location to the next inspection device is obtained, and the distance is divided by the appropriate travel time to obtain the target speed.

[0012] In one embodiment, the method further includes: If the next inspection device is not the reference device, then the current time to the first estimated time is determined as the inspection movement period, and the path from the actual location in the target inspection path to the next inspection device is determined as the inspection sub-path; When the vertical distance from the device to be monitored to the inspection sub-path is not greater than the first preset distance, the device to be monitored is identified as an interfering device, and the device weight of a single interfering device is multiplied by the time period weight of the corresponding interfering time period to obtain the weight product corresponding to a single interfering device. The interfering time period is the time period to be monitored included in the inspection movement time period. The weighted products of each of the interference devices are summed to obtain a comprehensive result. If the comprehensive result is not greater than a preset result threshold, the inspection sub-path is determined to have passed the verification.

[0013] A second aspect of this application provides an inspection robot inspection system, specifically including: The information acquisition module is used to acquire the actual location of the target inspection robot in the target wind power station, and to acquire multiple first historical energy devices that have experienced faults in the target wind power station and the types of historical faults that have occurred in the first historical energy devices. The impact assessment module is used to identify multiple energy devices to be inspected from the multiple first historical energy devices, and to determine the fault impact value of the energy devices to be inspected based on the historical fault types that have occurred in the energy devices to be inspected. The fault impact value characterizes the impact of the fault of the energy devices to be inspected on the overall operation of the target wind power station. The path determination module is used to determine the energy equipment to be inspected as a key inspection equipment if the fault impact value is greater than a preset impact value threshold, and to determine the energy equipment to be inspected as a candidate inspection equipment if the fault impact value is not greater than the impact value threshold. The module also determines the inspection sequence of the key inspection equipment according to the fault impact value of each key inspection equipment, and determines multiple initial inspection paths according to the actual location, the equipment location of each key inspection equipment, and the inspection sequence. The path filtering module is used to obtain the actual wind direction of the target wind power station, select the target inspection path from the multiple initial inspection paths according to the actual wind direction, and obtain multiple second historical energy devices in the target wind power station that have caused electromagnetic interference to the inspection robot within a first preset distance and the historical time period of the electromagnetic interference caused by the second historical energy devices. The target inspection path is the initial inspection path of the target inspection robot that is least affected by wind resistance. The equipment inspection module is used to optimize the target inspection path based on the multiple second historical energy devices, the historical time period, and the alternative inspection devices to obtain the final inspection path, and control the target inspection robot to perform energy equipment inspection on the target wind power station according to the final inspection path.

[0014] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when loaded and executed by a processor, performs the steps of the method described in any one of the first aspects.

[0015] A fourth aspect of this application provides an electronic device, specifically comprising: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, the processor being configured to load and execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of the first aspects.

[0016] In summary, this application includes at least one of the following beneficial technical effects: Based on the fault impact value of key inspection equipment, a corresponding inspection sequence is determined. Then, combining the robot's actual position with the equipment positions of each key inspection device, multiple initial inspection paths are generated. This ensures that the inspection work prioritizes covering equipment with high fault impact, guaranteeing a focus on key areas and improving the targeting of inspections. Furthermore, considering the actual wind direction of the target wind power station, the target inspection path with the least wind resistance is selected from multiple initial inspection paths, effectively reducing the impact of wind direction on the operational stability and energy consumption of the inspection robot. Simultaneously, the historical data of the second historical energy equipment within the target wind power station that has caused electromagnetic interference to the inspection robot within a first preset distance, along with the historical time periods of such interference, are collected. This data is then combined with alternative inspection equipment to optimize the target inspection path, resulting in the final inspection path. This avoids the impact of electromagnetic interference on the operational accuracy of the inspection robot and the accuracy of inspection data, while fully utilizing alternative inspection equipment resources to achieve comprehensive inspection coverage. Finally, the inspection robot is controlled to perform inspection work according to the optimized final inspection path, making the inspection path planning more rational and accurate, thereby improving the inspection quality of the target inspection robot. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an inspection method using an inspection robot provided in an embodiment of this application. Figure 2 This is a schematic diagram illustrating the relationship between the devices requiring attention and the time periods requiring attention, provided in an embodiment of this application. Figure 3 This is a schematic diagram of the structure of an inspection robot inspection system provided in an embodiment of this application; Figure 4 This is a schematic diagram of another inspection robot inspection system provided in the embodiments of this application.

[0018] Explanation of reference numerals in the attached diagram: 11. Information acquisition module; 12. Impact assessment module; 13. Route determination module; 14. Route filtering module; 15. Equipment inspection module; 16. Route verification module. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0020] In the description of the embodiments of this application, words such as "exemplarily," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplarily," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of words such as "exemplarily," "for example," or "for instance" is intended to present the relevant concepts in a specific manner.

[0021] In the description of the embodiments of this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, B existing alone, or A and B existing simultaneously. Furthermore, unless otherwise stated, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0022] See Figure 1 This application discloses a flowchart of an inspection robot inspection method, which can be implemented using a computer program or run on an inspection robot inspection system based on the von Neumann architecture. The computer program can be integrated into an application or run as a standalone utility application, specifically including: S101: Obtain the actual location of the target inspection robot in the target wind power station, and obtain the first historical energy equipment that has experienced failures in the target wind power station and the types of historical failures that have occurred in the first historical energy equipment.

[0023] Specifically, in this embodiment, the target wind power station is a wind power station that requires inspection of its energy equipment. This energy equipment includes, but is not limited to, wind turbine generators, step-up transformers, data collectors, and high-voltage transmission equipment. Energy equipment refers to all types of machinery, devices, and complete systems that directly or indirectly participate in the entire process of energy production, conversion, transmission, storage, regulation, and utilization, realizing changes in energy form, spatial transfer, or efficient management. The target inspection robot is the inspection robot currently used to inspect the energy equipment within the target wind power station. This target inspection robot is a quadruped robot (wheeled and tracked with integrated intelligence), which, through multi-sensor perception, autonomous movement, and intelligent data analysis, achieves equipment operating status monitoring, fault hazard warning, and inspection data visualization. It is a core intelligent equipment for lean operation and maintenance of wind power stations and ensuring the safe and stable operation of energy equipment.

[0024] The inspection method for a patrol robot disclosed in this application uses the target patrol robot itself as the execution subject. In other embodiments, the execution subject can also be a server, which communicates wirelessly with the target patrol robot. The server is an independent physical server. One method for obtaining the actual location of the target patrol robot is to obtain its actual location through the GPS module built into the target patrol robot. Additionally, based on cached historical fault records, multiple first historical energy devices that have experienced faults and the historical fault types of these first historical energy devices are obtained. The historical fault records include, but are not limited to, information such as the energy devices that the target patrol robot discovered faults during historical inspections and the specific types of the faults.

[0025] S102: Identify multiple energy devices to be inspected from multiple first-historical energy devices, and determine the fault impact value of the energy devices to be inspected based on the historical fault types that have occurred in the energy devices to be inspected.

[0026] Specifically, the frequency of occurrence of a single historical energy device among all historical energy devices is counted. If the frequency exceeds a preset threshold, it indicates that the historical energy device in the target wind power station has experienced a high number of failures. Therefore, this historical energy device is identified as an energy device to be inspected, i.e., an energy device prone to failure. Further, the frequency of occurrence of a single historical failure type among the multiple historical failure types experienced by the single energy device to be inspected is counted. If the frequency exceeds a preset threshold, this historical failure type is identified as the failure type to be inspected for the single energy device to be inspected, i.e., a failure type that the single energy device to be inspected is prone to.

[0027] Furthermore, a first weight is determined for each individual energy device to be inspected. This first weight is the ratio of the frequency of occurrence of the individual energy device to the sum of the frequencies of occurrence of all energy devices to be inspected, representing the probability of the energy device malfunctioning. Then, a second weight is determined for each type of malfunction to be inspected corresponding to the energy device. This second weight is the ratio of the frequency of occurrence of a single malfunction type to the sum of the frequencies of occurrence of all malfunction types to be inspected, representing the probability of the energy device experiencing the corresponding malfunction type. Next, based on the equipment inspection records of the target inspection robot, the inspection frequency of the energy device to be inspected is compared with the total inspection frequency of all energy devices in the target wind power plant. The ratio of the inspection frequency to the total inspection frequency is determined as the importance coefficient of the energy device to be inspected. The higher the inspection frequency, the more important the energy device to be inspected is to the target wind power plant. It should be noted that wind power plant operation and maintenance procedures typically arrange higher inspection frequencies for critical core equipment.

[0028] Furthermore, the product of the first weight of a single energy device to be inspected and the second weight of each corresponding fault type to be inspected is calculated. The product represents the probability of the energy device to be inspected exhibiting the corresponding fault type. The largest product is selected from multiple products, and the influence coefficient of the fault type corresponding to the largest product on the operation of the energy device to be inspected is determined. The larger the influence coefficient, the greater the impact on the operation of the energy device to be inspected. Specifically, the influence coefficient can be determined through a preset coefficient matching table. The coefficient matching table includes the influence coefficients of a single energy device for different fault types, all of which are set based on human experience.

[0029] Furthermore, the maximum product, importance coefficient, and influence coefficient corresponding to the same energy equipment to be inspected are multiplied together to obtain the fault impact value of the energy equipment to be inspected, which characterizes the impact of the fault of the energy equipment to be inspected on the overall operation of the target wind power station.

[0030] S103: If the fault impact value is greater than the preset impact value threshold, the energy equipment to be inspected is identified as a key inspection equipment. If the fault impact value is not greater than the impact value threshold, the energy equipment to be inspected is identified as a candidate inspection equipment. Based on the fault impact value of each key inspection equipment, the corresponding inspection sequence of the key inspection equipment is determined. Based on the actual location, the equipment location of each key inspection equipment, and the inspection sequence, multiple initial inspection paths are determined.

[0031] Specifically, if the fault impact value is greater than the preset impact value threshold, it indicates that a fault in the corresponding energy equipment to be inspected would have a significant impact on the overall operation of the target wind power station, and thus it is identified as a key inspection equipment. Conversely, if the fault impact value is not greater than the impact value threshold, then the energy equipment to be inspected is identified as a candidate inspection equipment. Further, the preset 3D terrain data, actual location, equipment location of each key inspection equipment, and inspection sequence of the target wind power station are imported into ArcGIS Pro. ArcGIS Pro, combined with the terrain of the target wind power station, plans multiple initial inspection paths, which can be understood as complete paths that proceed sequentially from the actual location to each different key inspection equipment according to the inspection sequence.

[0032] S104: Obtain the actual wind direction of the target wind power station, select the target inspection path from multiple initial inspection paths based on the actual wind direction, and obtain multiple second historical energy devices in the target wind power station that have caused electromagnetic interference to the inspection robot within the first preset distance and the historical time periods during which the second historical energy devices caused electromagnetic interference.

[0033] Specifically, the target inspection path is the initial inspection path that minimizes the impact of wind resistance on the target inspection robot. The actual wind direction of the target wind farm is obtained using a pre-set wind direction sensor. Then, multiple initial inspection paths and actual wind directions are added using the pre-set WindFarmer tool. Finally, the target inspection path with the least wind resistance is selected. In other embodiments, the target inspection path can also be selected from multiple initial inspection paths using the pre-set ROS Navigation tool. This part is prior art and will not be elaborated further here.

[0034] After the target inspection path is determined, based on pre-cached historical electromagnetic interference records, multiple second-historical energy devices within the target wind power station that have caused electromagnetic interference to the inspection robot within a first preset distance are obtained, along with the historical time periods during which these devices caused electromagnetic interference. These historical electromagnetic interference records include, but are not limited to, information about the energy devices that have caused electromagnetic interference to the inspection robot within the first preset distance and the time periods during which the interference occurred. It should be noted that the operation of energy devices within the target wind power station generates various electromagnetic signals, such as power frequency electromagnetic fields, high-frequency electromagnetic radiation, corona discharge, and arc discharge. These unintended electromagnetic signals can cause signal superposition, clutter interference, and magnetic field coupling with the inspection robot's electronic systems, sensors, and communication / navigation modules, thereby interfering with the equipment's inspection and navigation.

[0035] S105: Based on multiple second historical energy devices, historical time periods, and alternative inspection devices, optimize the target inspection path to obtain the final inspection path, and control the target inspection robot to inspect the energy equipment of the target wind power station according to the final inspection path.

[0036] Specifically, the frequency of a single second historical energy device appearing repeatedly among multiple second historical energy devices is counted. If the frequency exceeds a preset first threshold, then that second historical energy device is identified as a device of concern, i.e., an energy device that is likely to cause electromagnetic interference to the inspection robot within a first preset distance. At least one device of concern exists. Next, the frequency of a single historical period appearing repeatedly within the historical period of electromagnetic interference from a single device of concern is counted. If the frequency exceeds a preset second threshold, then that historical period is identified as the period of concern corresponding to the single device of concern, i.e., a period that is likely to cause electromagnetic interference to the inspection robot. At least one period of concern exists.

[0037] Furthermore, the device weight of each individual device of interest is determined. The device weight is the ratio of the number of times a single device of interest recurs to the sum of the number of times all devices of interest recurs, representing the likelihood that the device of interest will cause electromagnetic interference to the inspection robot within a first preset distance. Then, the time period weight for each time period corresponding to the device of interest is determined. The time period weight is the ratio of the frequency of a single time period of interest recurs to the sum of the frequencies of all time periods of interest, representing the likelihood that the device of interest will cause electromagnetic interference to the inspection robot within the first preset distance during the corresponding time period of interest. For example, consider devices M, N, and Q that require attention. Device M appears 30 times, device N appears 20 times, and device Q appears 50 times. Therefore, the device weight of device M is 30 times / (30 + 20 + 50) = 0.3. Further, device M corresponds to attention time periods m1, m2, and m3; device N corresponds to attention time periods n1 and n2; and device Q corresponds to attention time periods q1 and q2. Attention time period m1 appears 25 times, attention time period m2 appears 35 times, and attention time period m3 appears 40 times. Therefore, the time period weight of attention time period m1 is 25 times / (25 + 35 + 40) = 0.25. See details in [link to relevant documentation]. Figure 2 .

[0038] The system uses a preset speed sensor to obtain the current actual speed of the target inspection robot. Using an electronic map tool, it determines the distance from the current target inspection robot to the next inspection device along the target inspection path. Dividing the distance by the actual speed yields the estimated time, which is then added to the current time to obtain the first estimated time to reach the next inspection device. The next inspection device is the next key inspection device located at the actual position along the target inspection path that needs to be inspected. It should be noted that the first preset distance is greater than the distance the inspection robot travels to inspect energy equipment.

[0039] Furthermore, if the time period corresponding to a single device of concern includes the first estimated time, then the device of concern is designated as a reference device, and the time period including the first estimated time is designated as the reference time period. The device weight of the reference device is multiplied by the time period weight of the reference time period to obtain a first risk coefficient for electromagnetic interference generated by the reference device, representing the likelihood of the reference device generating electromagnetic interference to the inspection robot at the first estimated time. If the first risk coefficient is greater than a preset threshold, it indicates a higher probability that the reference device will generate electromagnetic interference to the inspection robot at the first estimated time. Therefore, when the next inspection device is the reference device, the target inspection robot is more likely to experience electromagnetic interference when it arrives at the next inspection device at the first estimated time, leading to interference with fault detection and larger errors. To avoid this situation, the target inspection path needs to be optimized. One feasible implementation is as follows: The target inspection robot's battery management system obtains its current remaining power. If the remaining power exceeds a preset threshold, it indicates sufficient battery capacity. Then, from at least one alternative inspection device within a second preset distance from the target location, the one with the highest fault impact is selected as the supplementary inspection device. Finally, using a preset navigation tool, the paths from the target location to the supplementary inspection device and from the supplementary device to the next inspection device are determined—the first sub-path. The first and second sub-paths are then combined to obtain the final inspection path. This not only avoids electromagnetic interference issues when the target robot directly reaches the next inspection device but also expands the inspection range. The second sub-path is the path within the target inspection path excluding the path from the target location to the next inspection device.

[0040] If the actual remaining battery power is not greater than the battery threshold, it indicates that the target inspection robot's current battery power is relatively low. In this case, the target inspection path is directly determined as the final inspection path, and the current actual speed is adjusted downwards to obtain the target speed. One feasible approach is to adjust the actual speed to a preset value to obtain an initial speed. Then, divide the distance from the actual position to the next inspection device by the initial speed to obtain the estimated travel time for the target inspection robot to reach the next inspection device at the initial speed. Next, if the time period of concern corresponding to the next inspection device includes a second estimated time, then the time period of concern containing the second estimated time is determined as an important time period. The device weight of the next inspection device is multiplied by the time period weight of the important time period to obtain a second risk coefficient for electromagnetic interference from the next inspection device. The second risk coefficient characterizes the likelihood of the target inspection robot being subjected to electromagnetic interference from the next inspection device when it arrives at the next inspection device for equipment inspection. If the second risk coefficient is not greater than the preset coefficient threshold, it means that the target inspection robot is less likely to be affected by electromagnetic interference from the next inspection device when it reaches the next inspection device for equipment inspection. In this case, the initial speed is directly determined as the target speed. If the second estimated time is not included in the time period of concern corresponding to the next inspection device, it means that the target inspection robot is less likely to be affected by electromagnetic interference when it reaches the next inspection device. In this case, the initial speed is determined as the target speed. Subsequently, the target inspection robot moves to the next inspection device according to this target speed, which not only saves power but also avoids the problem of electromagnetic interference when reaching the next inspection device.

[0041] In other embodiments, the actual speed is adjusted downwards to obtain the target speed. One feasible approach is to multiply the device weight of the next inspection device with the time period weights of the corresponding arrival time periods to obtain multiple multiplication results. The multiplication results represent the probability that the next inspection device will cause electromagnetic interference to the inspection robot within a first preset distance during the corresponding arrival time period. The arrival time period is the period of concern after the first estimated time. The smallest multiplication result is selected from the multiplication results. If the smallest multiplication result is not greater than a preset coefficient threshold, the arrival time period corresponding to the smallest multiplication result is determined as the suitable arrival time period. The maximum arrival time is selected from the suitable arrival time periods, and the current time is subtracted from the maximum arrival time to obtain the suitable movement duration. Then, the distance from the actual position in the target inspection path to the next inspection device is divided by the suitable movement duration to obtain the target speed to which the actual speed needs to be adjusted downwards.

[0042] In another embodiment, if the next inspection device is not a reference device, it indicates that the target inspection robot is less likely to be subject to electromagnetic interference from the next inspection device when moving to it at its actual speed. Therefore, the path from the actual speed to the next inspection device in the target inspection path can be kept unchanged (the target inspection path is directly determined as the final inspection path). Further, the period from the current time to the first estimated time is defined as the inspection movement period, and the path from the actual position in the target inspection path to the next inspection device is defined as the inspection sub-path. Next, the vertical distance from the device of interest to the inspection sub-path is calculated using a preset ArcGIS tool. If the vertical distance is not greater than the first preset distance, it indicates that the corresponding device of interest will cause electromagnetic interference to the target inspection robot's navigation during its movement. Therefore, the corresponding device of interest is identified as an interfering device. Then, the device weight of a single interfering device is multiplied by the time period weight of the corresponding interference period to obtain the weight product corresponding to that single interfering device. The interference period is the time period of interest included in the inspection movement period. The weight product represents the likelihood of the interfering device causing electromagnetic interference to the target inspection robot within the corresponding interference period.

[0043] Furthermore, the weighted products of each interfering device are summed to obtain a comprehensive result. This comprehensive result characterizes the overall probability of the target inspection robot being subjected to electromagnetic interference from surrounding energy devices as it moves to the next inspection device. If the comprehensive result is not greater than a preset threshold, it indicates that the overall probability of being subjected to electromagnetic interference from surrounding energy devices during movement is relatively low, thus validating this inspection sub-path as reasonable and requiring no further adjustment or optimization. If the comprehensive result is greater than the threshold, the path from the actual location to the next inspection device is replanned using ArcGIS Pro tools until the comprehensive result is no greater than the threshold. It should be noted that if the path from the actual location to the next inspection location is adjusted, this logic can also be used to assess the overall probability of the target inspection robot being subjected to electromagnetic interference from surrounding energy devices while moving along the path, thereby verifying the path.

[0044] It should be noted that when the target inspection robot arrives at the next inspection device, the inspection order for each type of fault to be inspected for that device is determined. The higher the second weight of the fault type, the earlier it is inspected. Based on this order, the next device is inspected specifically. After the target inspection robot completes its inspection of the next device, its current position is redefined as its actual position. The next energy device to be inspected at the redefined actual position in the final inspection path is then redefined as the next inspection device. The final inspection path is then defined as the target inspection path. The process of obtaining the first estimated time for the target robot to reach the next device, and optimizing the target inspection path based on the first estimated time, device weight, time period weight, and alternative inspection devices is repeated. This real-time optimization of the path from the target robot to the next device is achieved.

[0045] The implementation principle of the inspection robot inspection method in this application embodiment is as follows: Based on the fault impact value of key inspection equipment, the corresponding inspection sequence is determined. Then, combined with the actual position of the robot and the equipment position of each key inspection equipment, multiple initial inspection paths are generated to ensure that the inspection work prioritizes the coverage of equipment with a high degree of fault impact, ensuring that the inspection focus is highlighted and improving the inspection targeting. Furthermore, combined with the actual wind direction of the target wind power station, the target inspection path with the least wind resistance is selected from multiple initial inspection paths, effectively reducing the impact of wind direction on the operational stability and energy consumption of the inspection robot. At the same time, the historical data of the second historical energy equipment that has generated electromagnetic interference to the inspection robot within a first preset distance in the target wind power station and the historical time period of the interference are collected. Combined with the alternative inspection equipment, the target inspection path is optimized to obtain the final inspection path. This not only avoids the impact of electromagnetic interference on the operational accuracy of the inspection robot and the accuracy of the inspection data, but also makes full use of the alternative inspection equipment resources to achieve comprehensive inspection coverage. Finally, the inspection robot is controlled to carry out inspection work according to the optimized final inspection path, making the inspection path planning more reasonable and accurate, thereby improving the inspection quality of the target inspection robot.

[0046] The following are system embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the system embodiments of this application, please refer to the method embodiments of this application.

[0047] Please see Figure 3 This is a schematic diagram of the inspection robot inspection system provided in this application embodiment. This inspection robot inspection system can be implemented as all or part of a system through software, hardware, or a combination of both. The system includes an information acquisition module 11, an impact assessment module 12, a path determination module 13, a path filtering module 14, and an equipment inspection module 15.

[0048] The information acquisition module 11 is used to acquire the actual location of the target inspection robot in the target wind power station, and to acquire multiple first historical energy devices that have experienced failures in the target wind power station and the types of historical failures that have occurred in the first historical energy devices. The impact assessment module 12 is used to identify multiple energy devices to be inspected from multiple first historical energy devices, and to determine the fault impact value of the energy devices to be inspected based on the historical fault types that have occurred in the energy devices to be inspected. The fault impact value characterizes the impact of the fault of the energy devices to be inspected on the overall operation of the target wind power station. The path determination module 13 is used to determine the energy equipment to be inspected as the key inspection equipment if the fault impact value is greater than the preset impact value threshold, and to determine the energy equipment to be inspected as the alternative inspection equipment if the fault impact value is not greater than the impact value threshold. It also determines the inspection sequence of the key inspection equipment according to the fault impact value of each key inspection equipment, and determines multiple initial inspection paths according to the actual location, the equipment location of each key inspection equipment and the inspection sequence. The path filtering module 14 is used to obtain the actual wind direction of the target wind power station, select the target inspection path from multiple initial inspection paths based on the actual wind direction, and obtain multiple second historical energy devices in the target wind power station that have caused electromagnetic interference to the inspection robot within the first preset distance and the historical time period of the second historical energy devices that have caused electromagnetic interference. The target inspection path is the initial inspection path that is least affected by wind resistance for the target inspection robot. The equipment inspection module 15 is used to optimize the target inspection path based on multiple second historical energy devices, historical time periods and alternative inspection devices to obtain the final inspection path, and control the target inspection robot to perform energy equipment inspection on the target wind power station according to the final inspection path.

[0049] Optional, the equipment inspection module 15 is specifically used for: Identify at least one device of concern from among multiple second historical energy devices; Based on the historical periods during which the equipment of concern causes electromagnetic interference to the inspection robot, at least one period of concern shall be identified. Calculate the equipment weight of the equipment to be monitored, and calculate the time period weight of each time period to be monitored. The equipment weight represents the likelihood of the equipment to be monitored causing electromagnetic interference to the inspection robot, and the time period weight represents the likelihood of the equipment to be monitored causing interference to the inspection robot within the corresponding time period to be monitored. The first estimated time for the target inspection robot to reach the next inspection device is obtained. Based on the first estimated time, device weight, time period weight, and alternative inspection devices, the target inspection path is optimized to obtain the final inspection path. The next inspection device is the next key inspection device that needs to be inspected at the actual location in the target inspection path.

[0050] Optional, the equipment inspection module 15 is specifically used for: If the period of attention corresponding to the device to be monitored includes the first estimated time, then the device to be monitored is determined as the reference device, and the period of attention including the first estimated time is determined as the reference period. The first risk coefficient for electromagnetic interference generated by the reference device is obtained by multiplying the device weight of the reference time period by the time period weight. When the first risk coefficient is greater than the preset coefficient threshold, determine whether the next inspection device is a reference device; If the next inspection device is a reference device, the current actual remaining power of the target inspection robot is obtained. Based on the actual remaining power and the alternative inspection devices, the target inspection path is optimized to obtain the final inspection path.

[0051] Optional, the equipment inspection module 15 is specifically used for: When the actual remaining power is greater than the preset power threshold, the supplementary inspection device with the largest fault impact value is selected from at least one alternative inspection device within the second preset distance of the actual location, and the first sub-path is determined. The first sub-path and the second sub-path are combined to obtain the final inspection path. The first sub-path includes the path from the actual location to the supplementary inspection device and the path from the supplementary inspection device to the next inspection device. The second sub-path is the path in the target inspection path other than the path from the actual location to the next inspection device. When the actual remaining power is not greater than the preset power threshold, the current actual speed of the target inspection robot is reduced to obtain the target speed, and the target inspection path is determined as the final inspection path.

[0052] Optional, the equipment inspection module 15 is specifically used for: The current actual speed of the target inspection robot is reduced by a preset value to obtain the initial speed, and the distance from the actual position to the next inspection device is obtained. Divide the distance by the initial speed to obtain the estimated travel time of the target inspection robot. Based on the current time and the estimated travel time, obtain the second estimated time. If the second estimated time is included in the time period corresponding to the next inspection equipment, the time period that includes the second estimated time will be identified as an important time period. Multiply the equipment weight of the next inspection equipment by the time period weight of the important time period to obtain the second risk coefficient of electromagnetic interference generated by the next inspection equipment. If the second risk coefficient is not greater than the preset coefficient threshold, then the initial speed is determined as the target speed; If the second estimated time is not included in the time period corresponding to the next inspection equipment, the initial speed will be determined as the target speed.

[0053] Optional, the equipment inspection module 15 is specifically used for: The equipment weight of the next inspection equipment is multiplied by the time period weight of each time period to be arrived, resulting in multiple multiplication results. The time period to be arrived is the time period to be monitored after the first estimated time. Select the minimum multiplication result from all multiplication results, and when the minimum multiplication result is not greater than the preset coefficient threshold, determine the time period to be arrived corresponding to the minimum multiplication result as the appropriate time period to arrive; Select the maximum arrival time from the suitable arrival time period, and subtract the current time from the maximum arrival time to obtain the suitable travel time of the target inspection robot; Obtain the distance from the actual location to the next inspection device, divide the distance by the appropriate travel time, and get the target speed.

[0054] Optional, such as Figure 4 As shown, the system also includes a path verification module 16, which is specifically used for: If the next inspection device is not a reference device, then the period from the current time to the first estimated time is determined as the inspection movement period, and the path from the actual location in the target inspection path to the next inspection device is determined as the inspection sub-path. When the vertical distance from the device to be monitored to the inspection sub-path is not greater than the first preset distance, the device to be monitored is identified as an interfering device. The device weight of a single interfering device is multiplied by the time period weight of the corresponding interfering time period to obtain the weight product corresponding to a single interfering device. The interfering time period is the time period to be monitored included in the inspection movement time period. The weighted products of each interfering device are summed to obtain a comprehensive result. If the comprehensive result is not greater than the preset result threshold, the inspection sub-path verification is deemed successful.

[0055] It should be noted that the inspection robot inspection system provided in the above embodiments is only illustrated by the division of the above functional modules when executing the inspection robot inspection method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the equipment can be divided into different functional modules to complete all or part of the functions described above. In addition, the inspection robot inspection system and the inspection robot inspection method embodiment provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiment, which will not be repeated here.

[0056] This application also discloses a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements an inspection robot inspection method according to the above embodiments.

[0057] The computer program can be stored in a computer-readable medium. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or certain middleware. The computer-readable medium includes any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the computer-readable medium includes, but is not limited to, the above-mentioned components.

[0058] The inspection robot inspection method of the above embodiment is stored in the computer-readable storage medium and loaded and executed on the processor to facilitate the storage and application of the above method.

[0059] This application also discloses an electronic device in which a computer program is stored in a computer-readable storage medium. When the computer program is loaded and executed by a processor, it implements the above-mentioned inspection method for an inspection robot.

[0060] The electronic device can be a desktop computer, a laptop computer, or a cloud server, and includes, but is not limited to, a processor and a memory. For example, the electronic device may also include input / output devices, network access devices, and buses.

[0061] The processor can be a central processing unit (CPU). Of course, depending on the actual use, it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc., and this application does not limit it.

[0062] The memory can be an internal storage unit of an electronic device, such as a hard disk or RAM, or an external storage device, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD), or flash memory card (FC) equipped on the electronic device. Furthermore, the memory can be a combination of an internal storage unit and an external storage device. The memory is used to store computer programs and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or will be output. This application does not limit this.

[0063] In this electronic device, the inspection method of the inspection robot described in the above embodiment is stored in the memory of the electronic device and loaded and executed on the processor of the electronic device for convenient use.

[0064] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for inspection by a patrol robot, characterized in that, The method includes: Obtain the actual location of the target inspection robot in the target wind power station, and obtain multiple first historical energy devices that have experienced failures in the target wind power station and the types of historical failures that have occurred in the first historical energy devices; Multiple energy devices to be inspected are identified from the multiple first historical energy devices, and the failure impact value of the energy devices to be inspected is determined according to the historical failure types of the energy devices to be inspected. The failure impact value characterizes the impact of the failure of the energy devices to be inspected on the overall operation of the target wind power station. If the fault impact value is greater than the preset impact value threshold, the energy equipment to be inspected is identified as a key inspection equipment. If the fault impact value is not greater than the impact value threshold, the energy equipment to be inspected is identified as a candidate inspection equipment. Based on the fault impact value of each key inspection equipment, the inspection sequence of the corresponding key inspection equipment is determined. Based on the actual location, the equipment location of each key inspection equipment, and the inspection sequence, multiple initial inspection paths are determined. The actual wind direction of the target wind power station is obtained. Based on the actual wind direction, a target inspection path is selected from the multiple initial inspection paths. Multiple second historical energy devices in the target wind power station that have caused electromagnetic interference to the inspection robot within a first preset distance and the historical time periods during which the second historical energy devices caused electromagnetic interference are obtained. The target inspection path is the initial inspection path that is least affected by wind resistance for the target inspection robot. Based on the multiple second historical energy devices, the historical time period, and the alternative inspection devices, the target inspection path is optimized to obtain the final inspection path, and the target inspection robot is controlled to perform energy equipment inspection on the target wind power station according to the final inspection path.

2. The inspection method of the inspection robot according to claim 1, characterized in that, The optimization of the target inspection path based on the plurality of second historical energy devices, the historical time period, and the alternative inspection devices to obtain the final inspection path specifically includes: Identify at least one device of concern from the plurality of second historical energy devices; Based on the historical periods during which the devices of concern cause electromagnetic interference to the inspection robot, at least one period of concern is identified. Calculate the device weight of the device to be monitored and calculate the time period weight of each time period to be monitored. The device weight represents the likelihood of the device to be monitored causing electromagnetic interference to the inspection robot, and the time period weight represents the likelihood of the device to be monitored causing interference to the inspection robot within the corresponding time period to be monitored. The first estimated time for the target inspection robot to reach the next inspection device is obtained. Based on the first estimated time, the device weight, the time period weight, and the alternative inspection devices, the target inspection path is optimized to obtain the final inspection path. The next inspection device is the next key inspection device that needs to be inspected at the actual position in the target inspection path.

3. The inspection method of the inspection robot according to claim 2, characterized in that, The step of optimizing the target inspection path based on the first estimated time, the equipment weight, the time period weight, and the candidate inspection equipment to obtain the final inspection path specifically includes: If the period of time corresponding to the device of concern includes the first estimated time, then the device of concern is determined as a reference device, and the period of time of concern including the first estimated time is determined as a reference period. The device weight of the reference device is multiplied by the time period weight of the reference time period to obtain the first risk coefficient of electromagnetic interference generated by the reference device. When the first risk coefficient is greater than the preset coefficient threshold, determine whether the next inspection device is the reference device; If the next inspection device is the reference device, then the current actual remaining power of the target inspection robot is obtained, and the target inspection path is optimized based on the actual remaining power and the alternative inspection devices to obtain the final inspection path.

4. The inspection method of the inspection robot according to claim 3, characterized in that, The step of optimizing the target inspection path based on the actual remaining power and the alternative inspection equipment to obtain the final inspection path specifically includes: When the actual remaining power is greater than a preset power threshold, a supplementary inspection device with the largest fault impact value is selected from at least one alternative inspection device within a second preset distance of the actual location, and a first sub-path is determined. The first sub-path and the second sub-path are combined to obtain the final inspection path. The first sub-path includes the path from the actual location to the supplementary inspection device and the path from the supplementary inspection device to the next inspection device. The second sub-path is the path in the target inspection path other than the path from the actual location to the next inspection device. When the actual remaining power is not greater than the preset power threshold, the current actual speed of the target inspection robot is reduced to obtain the target speed, and the target inspection path is determined as the final inspection path. The process of controlling the target inspection robot to perform energy equipment inspection on the target wind power station according to the final inspection path specifically includes: Based on the target speed, the target inspection robot is controlled to inspect the energy equipment of the target wind power station according to the final inspection path.

5. The inspection method of the inspection robot according to claim 4, characterized in that, The process of adjusting the current actual speed of the target inspection robot to obtain the target speed specifically includes: The current actual speed of the target inspection robot is reduced by a preset value to obtain an initial speed, and the distance from the actual position to the next inspection device is obtained; Divide the distance by the initial speed to obtain the estimated travel time of the target inspection robot, and obtain the second estimated time based on the current time and the estimated travel time; When the second estimated time is included in the time period of concern corresponding to the next inspection equipment, the time period of concern that includes the second estimated time is determined as an important time period; The equipment weight of the next inspection equipment is multiplied by the time period weight of the important time period to obtain the second risk coefficient of electromagnetic interference generated by the next inspection equipment. If the second risk coefficient is not greater than the preset coefficient threshold, then the initial speed is determined as the target speed; If the second estimated time is not included in the time period of concern corresponding to the next inspection equipment, the initial speed is determined as the target speed.

6. The inspection method of the inspection robot according to claim 4, characterized in that, The step of adjusting the current actual speed of the target inspection robot to obtain the target speed further includes: The equipment weight of the next inspection equipment is multiplied by the time period weight of each time period to be arrived, resulting in multiple multiplication results. The time period to be arrived is the time period to be monitored after the first estimated time. The minimum multiplication result is selected from all the multiplication results, and when the minimum multiplication result is not greater than a preset coefficient threshold, the time period to be arrived corresponding to the minimum multiplication result is determined as the appropriate time period to arrive. Select the maximum arrival time from the suitable arrival time periods, and subtract the current time from the maximum arrival time to obtain the suitable travel time of the target inspection robot; The distance from the actual location to the next inspection device is obtained, and the distance is divided by the appropriate travel time to obtain the target speed.

7. The inspection method of the inspection robot according to claim 3, characterized in that, The method further includes: If the next inspection device is not the reference device, then the current time to the first estimated time is determined as the inspection movement period, and the path from the actual location in the target inspection path to the next inspection device is determined as the inspection sub-path; When the vertical distance from the device to be monitored to the inspection sub-path is not greater than the first preset distance, the device to be monitored is identified as an interfering device, and the device weight of a single interfering device is multiplied by the time period weight of the corresponding interfering time period to obtain the weight product corresponding to a single interfering device. The interfering time period is the time period to be monitored included in the inspection movement time period. The weighted products of each of the interference devices are summed to obtain a comprehensive result. If the comprehensive result is not greater than a preset result threshold, the inspection sub-path is determined to have passed the verification.

8. An inspection robot inspection system, characterized in that, include: The information acquisition module (11) is used to acquire the actual location of the target inspection robot in the target wind power station, and to acquire multiple first historical energy devices that have experienced faults in the target wind power station and the types of historical faults that have occurred in the first historical energy devices. Impact assessment module (12) is used to identify multiple energy devices to be inspected from the multiple first historical energy devices, and to determine the fault impact value of the energy devices to be inspected based on the historical fault types that have occurred in the energy devices to be inspected. The fault impact value characterizes the impact of the fault of the energy devices to be inspected on the overall operation of the target wind power station. The path determination module (13) is used to determine the energy equipment to be inspected as a key inspection equipment if the fault impact value is greater than the preset impact value threshold, and to determine the energy equipment to be inspected as a candidate inspection equipment if the fault impact value is not greater than the impact value threshold. The module also determines the inspection sequence of the key inspection equipment according to the fault impact value of each key inspection equipment, and determines multiple initial inspection paths according to the actual location, the equipment location of each key inspection equipment, and the inspection sequence. The path filtering module (14) is used to obtain the actual wind direction of the target wind power station, select the target inspection path from the multiple initial inspection paths according to the actual wind direction, and obtain multiple second historical energy devices in the target wind power station that have caused electromagnetic interference to the inspection robot within a first preset distance and the historical time period during which the second historical energy devices caused electromagnetic interference. The target inspection path is the initial inspection path of the target inspection robot that is least affected by wind resistance. The equipment inspection module (15) is used to optimize the target inspection path based on the multiple second historical energy devices, the historical time period and the alternative inspection devices to obtain the final inspection path, and control the target inspection robot to perform energy equipment inspection on the target wind power station according to the final inspection path.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is loaded and executed by the processor, it implements the method of any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor loads and executes the computer program, it implements the method of any one of claims 1-7.

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