A factory intelligent operation and maintenance inspection method and system

Abstract

The present invention relates to the field of operation and maintenance inspection technology, and discloses a factory intelligent operation and maintenance inspection method and system thereof, wherein one factory intelligent operation and maintenance inspection method includes the following steps: establishing an inspection area and photovoltaic panel coordinates, generating a first route path, a drone inspecting the photovoltaic panels and bus cables according to the first route path, using a field camera to shoot the inspection area, determining whether there are hidden danger behaviors in the recorded video, using the photovoltaic panel coordinates to assist in locating the coordinates of the hidden danger behaviors, and generating a second route path based on the inspection area, photovoltaic panel coordinates, and coordinate planning of the hidden danger behaviors. The present invention uses the coordinates of the photovoltaic panels to estimate the coordinate position of the sheep when they are grazing or resting at the bus cables, thereby modifying the first route path based on the estimated coordinates of the sheep grazing or resting to generate a second route path, and focusing on inspecting the coordinates of the sheep grazing or resting through the second route path, thereby improving the cruising efficiency.

Description

Technical Field

[0001] The present invention relates to the field of operation and maintenance inspection technology, and specifically to a factory intelligent operation and maintenance inspection method and system. Background Art

[0002] PV power station inspections are crucial for ensuring the efficient and stable operation of PV systems. A comprehensive and scientific inspection system is essential. The following is a detailed description of PV power station inspections. PV power station inspections primarily encompass equipment inspection, technology application, and operations and maintenance management. Equipment inspections focus on surface cleanliness, hidden cracks, and hot spot effects on PV modules. Infrared thermal imagers should be used to regularly monitor module temperature distribution. Inverters should be inspected for operating indicators, cooling fan operation, and output parameter stability. Cable connectors and combiner boxes should be inspected for insulation performance and temperature rise. Mounting systems should be checked for structural stability and the condition of the anti-corrosion coating. Modern PV power stations commonly use drone inspections combined with AI image recognition technology to quickly detect module anomalies. Intelligent monitoring systems collect real-time operating data from various devices, providing fault warnings. Infrared thermal imaging technology can accurately locate potential hazards such as poor electrical connections. For operations and maintenance management, a tiered inspection system consisting of daily inspections, monthly tests, and annual inspections is essential. Professional inspection tools and protective equipment should be deployed, and detailed inspection records and equipment health records should be maintained.

[0003] Existing photovoltaic power stations consist of two parts: an outdoor part and an indoor part. The outdoor part includes photovoltaic panels, busbars, and a combiner box. Photovoltaic panels and combiner boxes are generally installed on the ground, and the busbars are usually buried in the ground to increase their service life. To facilitate maintenance, the depth is generally 700mm-1000mm. When the outdoor part needs to be inspected on rainy days, drones equipped with cameras are used for inspection. However, existing drone operation and maintenance inspections cannot detect whether potholes on the ground touch the busbars. Secondly, when a place needs maintenance, only the coordinates can be sent, and manual labor is required to slowly search for the maintenance site based on the coordinates, which can easily delay emergency repairs. Summary of the Invention

[0004] The present invention provides a factory intelligent operation and maintenance inspection method and system, which has the beneficial effect of quickly discovering places that need maintenance and marking them for personnel to find. It solves the problem mentioned in the above background technology that the existing drone operation and maintenance inspection cannot observe whether potholes generated on the ground touch the bus wires. Secondly, when a place that needs maintenance is found, only the coordinates can be sent, and manual labor is required to slowly search for the maintenance place based on the coordinates, which easily delays the emergency repair time.

[0005] The present invention provides the following technical solution: a factory intelligent operation and maintenance inspection method, comprising the following steps:

[0006] An inspection area and photovoltaic panel coordinates are established to generate a first flight path, and the drone inspects the photovoltaic panels and bus cables according to the first flight path;

[0007] Use site cameras to shoot inspection areas and generate recorded videos;

[0008] Determining whether a potential danger behavior exists in the recorded video, using the photovoltaic panel coordinates to assist in locating the coordinates of the potential danger behavior, and planning and generating a second flight path based on the inspection area, the photovoltaic panel coordinates, and the coordinates of the potential danger behavior;

[0009] The drone is equipped with a detection device and moves to the location of the potential danger behavior, and uses the detection device to determine whether there is a potential danger at the location of the potential danger behavior;

[0010] When a hidden danger is confirmed, the drone dumps paint to mark the hidden danger and uploads the coordinates of the confirmed hidden danger.

[0011] As an optional solution of the factory intelligent operation and maintenance inspection method and system thereof of the present invention, wherein: marking the coordinates of the bus cable that coincide with the location of the hidden danger behavior;

[0012] A cable pre-buried threshold is set, and when the detection device detects that the land depth data of the coincident coordinates is greater than or equal to the cable pre-buried threshold, it is determined that there is a hidden danger at the coordinates;

[0013] The distance between the detection device and the ground is equal to the set flight altitude.

[0014] As an optional solution of the factory intelligent operation and maintenance inspection method and system thereof of the present invention, wherein: the inclination of rainwater is determined according to wind direction, and the flight attitude of the UAV in the rainwater is adjusted;

[0015] Adjust the angle of the detection equipment according to the inclination of the rain and plan a path close to the potential danger behavior.

[0016] As an optional solution of the factory intelligent operation and maintenance inspection method and system thereof of the present invention, wherein: the detection equipment includes a mobile camera, an ultrasonic sensor, a laser sensor, a Hall effect sensor and an infrared thermal imager;

[0017] The mobile camera is used to capture images of land depressions;

[0018] The ultrasonic sensor and laser sensor detect the depth data of land depression;

[0019] The Hall effect sensor detects leakage data;

[0020] The temperature sensor detects whether there is a severe fever.

[0021] As an optional solution of the factory intelligent operation and maintenance inspection method and system of the present invention, it further includes historical data, wherein the historical data records the coordinates of previous maintenance locations;

[0022] A maintenance frequency threshold is set, and when the previous maintenance position coordinates are greater than or equal to the maintenance frequency threshold, the previous maintenance position coordinates are selected, and auxiliary planning is performed based on the selected previous maintenance position coordinates to generate a second flight path.

[0023] As an optional solution of the factory intelligent operation and maintenance inspection method and system of the present invention, wherein: an image is captured by a mobile camera according to the coordinates of the hidden danger behavior, the image is pixelated, and the image size is confirmed by a scale using the flight altitude and the pixels of the image, thereby confirming the opening perimeter of the hidden danger location;

[0024] The drone dumps paint markings according to the opening perimeter of the hidden danger location.

[0025] As an optional solution of the factory intelligent operation and maintenance inspection method and system thereof of the present invention, wherein: the dumping ratio is adjusted according to the opening perimeter of the hidden danger location;

[0026] A paint dumping path is planned according to the coordinate digital image of the hidden danger location, and the paint dumping path is the same as the coordinate digital image of the hidden danger location.

[0027] As an optional solution of the factory intelligent operation and maintenance inspection method and system thereof of the present invention, wherein: the second flight path includes a flight path and a detection path;

[0028] The flight path includes the path between the current path point of the drone and the path point near the hidden danger;

[0029] The detection path includes a path between a path point near a hidden danger and a path point at the hidden danger;

[0030] Determine the coordinates of the potential danger behavior and the next flight path connected to it;

[0031] The next flight path is used to blow away water drops on the detection equipment.

[0032] As an optional solution of the factory intelligent operation and maintenance inspection method and system thereof of the present invention, wherein: the pigment marking has three color markings of red, yellow and blue;

[0033] Red paint marks indicate danger and require power outage for repairs;

[0034] Yellow paint marks indicate doubts and require detailed inspection of potential hazards;

[0035] Blue paint marks indicate safety and the potential hazard needs to be reburied

[0036] The present invention also provides a system for applying a factory intelligent operation and maintenance inspection method, comprising:

[0037] A generation module determines the coordinates of the photovoltaic panels and the busbar cables of the photovoltaic power station, generates an inspection area, and determines a first flight path based on the inspection area;

[0038] A shooting module records the video of the photovoltaic panels and the bus cable in real time, and determines the coordinates of the hidden danger behavior through the coordinates of the photovoltaic panels and the bus cable;

[0039] A detection module, which determines whether there is a hidden danger at the hidden danger behavior location through the detection module, and modifies the first flight path to generate a second flight path based on the detected danger;

[0040] A storage module, the storage module is used to store the video captured by the shooting module and historical maintenance data;

[0041] The marking module stores three colors of pigments, and marks corresponding to different risks are created by pouring different colors of pigments.

[0042] The present invention has the following beneficial effects:

[0043] 1. The factory's intelligent operation and maintenance inspection method and system infers the coordinates of the sheep grazing or resting at the busbar based on the coordinates of the photovoltaic panels. Based on the inferred coordinates of the sheep grazing or resting, the first route is modified to generate a second route. The second route is used to focus on inspecting the coordinates of the sheep grazing or resting, thereby improving patrol efficiency.

[0044] 2. The factory's intelligent operation and maintenance inspection method and system pours paint onto the coordinates of potential hazards, allowing maintenance personnel to first find the X-axis coordinate point and then observe the position of the paint mark on the ground along the Y-axis direction. There is no need to confirm each Y-axis coordinate point one by one, thereby improving subsequent maintenance efficiency and increasing emergency repair time.

[0045] 3. The factory's intelligent operation and maintenance inspection method and system adjusts the drone's flight speed, sets the speed of the next flight path to the maximum flight speed limit, and uses wind resistance to blow away water droplets on the inspection equipment, thereby improving the quality of subsequent inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a schematic diagram of the architecture of the intelligent operation and maintenance inspection method of the present invention.

[0047] Figure 2 This is a schematic diagram of the UI interface of the intelligent operation and maintenance inspection platform of the present invention. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0049] Example 1

[0050] See also Figure 1-Figure 2 , one of the factory intelligent operation and maintenance inspection methods includes the following steps:

[0051] Establish inspection areas and photovoltaic panel coordinates, generate a first flight path, and the drone inspects the photovoltaic panels and bus cables along the first flight path;

[0052] Use site cameras to shoot inspection areas and generate recorded videos;

[0053] Determine if there are any hidden dangers in the recorded video, use the photovoltaic panel coordinates to assist in locating the coordinates of the hidden danger, and plan and generate a second flight path based on the inspection area, photovoltaic panel coordinates, and the coordinates of the hidden danger;

[0054] The drone is equipped with detection equipment and moves to the location of the potential danger behavior. The detection equipment is used to determine whether there is a potential danger at the location of the potential danger behavior.

[0055] When a hidden danger is confirmed, the drone dumps paint to mark the hidden danger and uploads the coordinates of the confirmed hidden danger.

[0056] Existing photovoltaic power stations consist of two parts: an outdoor part and an indoor part. The outdoor part includes photovoltaic panels, busbars, and a combiner box. Photovoltaic panels and combiner boxes are generally installed on the ground, and the busbars are usually buried in the ground to increase their service life. To facilitate maintenance, the depth is generally 700mm-1000mm. When the outdoor part needs to be inspected on rainy days, drones equipped with cameras are used for inspection. However, existing drone operation and maintenance inspections cannot detect whether potholes on the ground touch the busbars. Secondly, when a place needs maintenance, only the coordinates can be sent, and manual labor is required to slowly search for the maintenance site based on the coordinates, which can easily delay emergency repairs.

[0057] Hazardous behaviors include sheep grazing and digging holes near busbars when shepherding, rats digging holes near busbars, geological changes, and previous busbar repairs. These situations may cause busbars to be exposed when washed away by rainwater.

[0058] When the sheep are grazing or resting near the busbar, record them with the field camera;

[0059] Coordinates are assigned to each photovoltaic panel in turn, and the coordinates of the sheep are estimated based on the coordinates of the photovoltaic panels when they are grazing or resting at the busbar. The first route is modified based on the estimated coordinates of the sheep grazing or resting to generate a second route. The second route is used to focus on the coordinates of the sheep grazing or resting, thereby improving patrol efficiency;

[0060] It should be noted that the path planning is performed according to the UAV path planning algorithm, wherein the UAV path planning algorithm includes the greedy algorithm, the ant algorithm, etc.

[0061] For two-dimensional or regularly gridded three-dimensional maps, greedy algorithms can quickly converge to a feasible solution by combining heuristic rules (such as the shortest Euclidean distance);

[0062] The ant algorithm explores multiple paths through the positive feedback mechanism of pheromones, avoiding falling into local optimality. It is particularly suitable for global path planning in complex three-dimensional environments (such as forests and mountains);

[0063] Potholes can be formed by sheep grazing and digging holes, rats digging holes, geological changes, and rainwater erosion at busbars where repairs have occurred. These holes can be filled with rainwater, and the mobile cameras on drones cannot clearly determine whether there are hidden dangers. Therefore, detection equipment is installed on drones.

[0064] Detection equipment includes mobile cameras, ultrasonic sensors, laser sensors, Hall effect sensors, and infrared thermal imagers;

[0065] The mobile camera is used to capture images of the land depression, thereby capturing images of the opening of the land depression;

[0066] Ultrasonic sensors and laser sensors detect land depression depth data;

[0067] The Hall effect sensor detects leakage data. When leakage occurs, the Hall effect sensor is used to detect whether there is leakage.

[0068] The temperature sensor detects whether there is heating. When a fault occurs or the circuit is damaged, high temperature will occur. Therefore, the temperature sensor is used to assist the Hall effect sensor to determine whether there is leakage or severe heating.

[0069] When a pothole or ground line problem is confirmed, the coordinates of the location will be marked as a potential hazard and uploaded for maintenance personnel to repair based on the coordinates.

[0070] Furthermore, since the outdoor area of ​​the photovoltaic power station covers hundreds to thousands of acres, there are coordinates of hidden dangers, and the photovoltaic panels are used as a reference. However, it is time-consuming to find the coordinates of the hidden dangers among the numerous X-axis or Y-axis coordinate points. Therefore, a paint pouring device is installed at the lower end of the drone. By pouring paint onto the coordinates of the hidden dangers, maintenance personnel can first find the X-axis coordinate point, and then observe the position of the paint mark on the ground along the Y-axis direction. There is no need to confirm the Y-axis coordinate points one by one, thereby improving the subsequent maintenance efficiency and increasing the repair time.

[0071] Example 2

[0072] This embodiment is an improvement made on the basis of embodiment 1. For details, please refer to Figure 1-Figure 2 , mark the coordinates where the busbar cable coincides with the location of the hidden danger behavior;

[0073] Set the cable pre-buried threshold. When the detection equipment detects that the land depth data of the overlapping coordinates is greater than or equal to the cable pre-buried threshold, it is determined that there is a hidden danger at the coordinates.

[0074] The distance between the detection equipment and the ground is equal to the set flight altitude.

[0075] Input the busbar cable construction drawing to determine the coordinates of the busbar cable;

[0076] A mobile camera captures an image of the opening of the land depression, or a temperature sensor detects whether there is heating. Based on the image or detection, the coordinates of the photovoltaic panel are used as a reference to estimate the approximate coordinates. When the error between the estimated approximate coordinates and the coordinates of the bus cable is small, it is determined that there is a hidden danger at the estimated approximate coordinates. This is marked to assist in modifying the first route and thus planning and generating a second route.

[0077] Furthermore, since the land where the bus cable is installed may be uneven and the bus cable needs to be buried more than 700mm in the ground, the flight altitude of the drone needs to be adjusted in real time. Only when the flight altitude is the same can the detection equipment carried by the drone perform accurate detection. Therefore, the bus cable is detected by ultrasonic sensors and laser sensors, and the bus cable is used as the detection reference point to determine the flight altitude between the drone and the ground, thereby improving the detection accuracy of the detection equipment carried by the drone.

[0078] Example 3

[0079] This embodiment is an improvement made on the basis of embodiment 2. For details, please refer to Figure 1-Figure 2 ,determine the inclination of rainwater according to wind direction and adjust the flight attitude of the UAV in the rainwater;

[0080] Adjust the angle of the detection equipment according to the inclination of the rain and plan a path close to the potential danger behavior.

[0081] Combined with weather software to obtain wind direction data to estimate the rainfall inclination angle, the angle of the drone is adjusted according to the rain inclination angle, so that the detection equipment can avoid most of the rain;

[0082] Since the bus cable may be far away from the position of the solar panel, the drone needs to detect and shoot in the rain. The path of approaching the potential danger behavior includes the drone being at the solar panel position closest to the potential danger behavior after angle adjustment, and then calibrating the coordinates of the potential danger behavior. The distance between the potential danger behavior and the current drone position is detected according to the tilt angle of the ultrasonic sensor and the laser sensor. This distance is the hypotenuse data, and the horizontal distance between the current horizontal distance of the drone and the detection potential danger behavior is the adjacent side data. At this time, the opposite side data is calculated by trigonometric function, and the detection height is constant. Therefore, the constant height is subtracted from the opposite side data to obtain the height position at which the current drone needs to descend. In this way, the drone under the solar panel does not need to adjust the flight altitude while detecting the height above the ground, so that the drone with adjusted altitude can quickly fly to the potential danger behavior limit detection, thereby improving the detection efficiency. After the detection is completed, the original route is returned to inspect the next potential danger behavior.

[0083] It should be noted that by tilting the ultrasonic sensor and laser sensor to detect the height above the ground in advance from a long distance, the drone can be smoothly adjusted from the current node height position to the next node height position. When the drone flies to the potential danger behavior, the ultrasonic sensor and laser sensor are adjusted again so that the ultrasonic sensor and laser sensor are perpendicular to the ground for easy detection.

[0084] Example 4

[0085] This embodiment is an improvement made on the basis of embodiment 3. For details, please refer to Figure 1-Figure 2 , also includes historical data, which records the coordinates of previous maintenance locations;

[0086] A maintenance frequency threshold is set. When the previous maintenance location coordinates are greater than or equal to the maintenance frequency threshold, the previous maintenance location coordinates are selected, and auxiliary planning is performed based on the selected previous maintenance location coordinates to generate a second route path.

[0087] The maintenance frequency threshold is 2 maintenances per week. If the previous maintenance location coordinates are ≥ 2 maintenances per week, the previous maintenance location coordinates are selected to modify the second route.

[0088] When the distance between the selected previous maintenance location coordinates and the coordinates of the hidden danger behavior location is not less than 5m-15m, the previous maintenance location coordinates here are inspected first to improve the inspection efficiency.

[0089] Example 5

[0090] This embodiment is an improvement made on the basis of embodiment 4. For details, please refer to Figure 1-Figure 2 ,According to the coordinates of the hidden danger behavior, the mobile camera is used to capture the image, pixelate the image, and use the flight altitude and the image pixels to confirm the graphic size through the scale, so as to confirm the opening perimeter of the hidden danger;

[0091] The drone dumps paint markings based on the opening perimeter of the potential hazard.

[0092] The mobile camera shoots vertically;

[0093] Since the flight altitude and focal length are determined, the image taken by the mobile camera is pixelated and the actual size of the object is calculated as follows:

[0094] ;

[0095] f is the focal length of the camera, H is the shooting height, d is the corresponding size in the image, and M is the scale;

[0096] For example, if the pixel length of an object in the image is 500 pixels, the camera focal length is 8 mm, and the flight altitude is H = 100 m, then the actual size is 500*(100 / 0.008)=6250000 mm=6.25 km;

[0097] The diameter of the opening at the hidden danger point is obtained through the above calculation, and the circumference of the opening at the hidden danger point is obtained through the circumference calculation formula;

[0098] Then, images of the potential danger site and the nearest photovoltaic panel are taken at the same height to calculate the distance between the potential danger site and the photovoltaic panel. Since the coordinates of the photovoltaic panel are determined, the distance between the potential danger site and the photovoltaic panel is obtained by adding or subtracting on the X or Y axis to obtain the coordinate position of the potential danger site.

[0099] It should be noted that when the potential danger point is not perpendicular or parallel to the photovoltaic panel, a vertical line and a horizontal line are set up. The horizontal line extends from the photovoltaic panel, and the vertical line extends from the center of the potential danger point. The vertical line and the horizontal line intersect to form an intersection. The distance from the intersection to the photovoltaic panel and the distance from the intersection to the center of the potential danger point are calculated using the above calculation formula. The data of the X-axis and Y-axis are added or deleted to obtain the distance between the potential danger point and the photovoltaic panel and the coordinate position of the potential danger point.

[0100] It should be noted that the row spacing of photovoltaic panels is 7 meters, and the adjacent spacing is 1 meter. Several photovoltaic panels are arranged in sequence, and the coordinates of the first photovoltaic panel are (0, 0);

[0101] The coordinates of the second photovoltaic panel on the X-axis are (1, 1), the coordinates of the third photovoltaic panel on the X-axis are (2, 1), and so on;

[0102] The coordinates of the second photovoltaic panel on the Y axis are (1, 8), the coordinates of the third photovoltaic panel on the Y axis are (2, 8), and so on;

[0103] The drone flies to the coordinates of the potential hazard and then pours the paint according to the circumference of the opening of the potential hazard. The paint is poured around the opening of the potential hazard in a circle, so as to achieve precise pouring of the paint to the potential hazard. The pouring range is around the circumference of the potential hazard, so a large amount of dye will be stained on the land at the potential hazard, thus reducing the possibility of the dye being washed away by rainwater and ensuring the integrity of the mark, making it easier for subsequent maintenance personnel to quickly find the mark.

[0104] It should be noted that the dyes are natural soil dyes that dissolve in the soil and will not cause pollution to the land.

[0105] Example 6

[0106] This embodiment is an improvement made on the basis of embodiment 5. For details, please refer to Figure 1-Figure 2 , adjust the dumping ratio according to the opening perimeter of the hidden danger area;

[0107] The paint dumping path is planned according to the coordinate digital image of the hidden danger location, and the paint dumping path is the same as the coordinate digital image of the hidden danger location.

[0108] In order to further improve the visibility of the marking, the opening perimeter mark around the hidden danger is changed to a digital mark of the same scale, and the numerical mark is an integer number of the X-axis or Y-axis coordinate position of the hidden danger;

[0109] Preferably, the perimeter markings around the opening of the hidden danger are changed to digital markings of larger than the same scale, so that the poured pigment is away from the opening of the hidden danger and the numbers are graffitied, thereby reducing the problem of dye loss caused by mud and water flowing through the opening of the hidden danger;

[0110] The second flight path includes a flight path and a detection path;

[0111] The flight path includes the path between the current path point of the drone and the path point near the hidden danger;

[0112] The detection path includes the path between the path point near the hidden danger and the path point at the hidden danger;

[0113] Determine the coordinates of the potential danger behavior and the next flight path connected to it;

[0114] The next leg of the flight path is used to blow away water droplets on the detection equipment.

[0115] When the drone flies to a hidden danger location without any obstructions and takes photos of the location, it returns along the original route. At this time, the drone and the detection equipment may be stuck with rain water, which will affect the detection of the next location. Therefore, the flight speed of the drone is adjusted, and the speed of the next flight path is set to the maximum flight speed limit. The wind resistance will blow away the water droplets on the detection equipment, thereby improving the quality of subsequent detections.

[0116] Specifically, the drone flies to a path point near the hidden danger, flies from the path point near the hidden danger to the coordinate point of the hidden danger for detection, and then returns to the path point near the hidden danger. The flight path from the current path point near the hidden danger to the next path point near the hidden danger is the flight path, and the speed of this flight path is the maximum flight speed limit.

[0117] Example 7

[0118] This embodiment is an improvement made on the basis of embodiment 6. For details, please refer to Figure 1-Figure 2 , pigment markers have three color markers: red, yellow and blue;

[0119] Red paint marks indicate danger and require power outage for repairs;

[0120] Yellow paint marks indicate doubts and require detailed inspection of potential hazards;

[0121] Blue paint marks indicate safety and the hidden danger area needs to be reburied.

[0122] Determine the risk result based on the detection data of Example 1,

[0123] When there is no photovoltaic-related equipment at the potential hazard site, but only a pothole, it is defined as safe and is indicated by dumping a blue mark;

[0124] When photovoltaic-related equipment exists near the potential hazard, and the Hall effect sensor and temperature sensor fail to detect serious leakage or heating problems, the location is considered doubtful and the suspicion is expressed by dumping yellow paint;

[0125] When there are photovoltaic-related equipment near the hidden danger, the Hall effect sensor and temperature sensor detect leakage or serious heat problems, and the location is considered suspicious, and red paint is poured to indicate danger;

[0126] The red pigment area is processed first, the yellow pigment area is processed second, and the blue pigment area is processed last.

[0127] Example 8

[0128] The present invention also provides a system for applying a factory intelligent operation and maintenance inspection method, comprising:

[0129] A generation module determines the coordinates of the photovoltaic panels and the busbar cables of the photovoltaic power station, generates an inspection area, and determines a first flight path based on the inspection area;

[0130] A shooting module records the video of the photovoltaic panels and the bus cable in real time, and determines the coordinates of the hidden danger behavior through the coordinates of the photovoltaic panels and the bus cable;

[0131] A detection module, which determines whether there is a hidden danger at the hidden danger behavior location through the detection module, and modifies the first flight path to generate a second flight path based on the detected danger;

[0132] A storage module is used to store the video captured by the shooting module and historical maintenance data;

[0133] The marking module stores three colors of pigments. Different colors of pigments are poured to mark the corresponding risks. The marking module includes a storage box, a nozzle and a water pump, which are connected by pipes.

[0134] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0135] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A factory intelligent operation and maintenance inspection method, characterized in that: The following steps are involved: An inspection area and photovoltaic panel coordinates are established to generate a first flight path, and the drone inspects the photovoltaic panels and bus cables according to the first flight path; Use site cameras to shoot inspection areas and generate recorded videos; Determine the potential danger behavior in the recorded video, use the photovoltaic panel coordinates to assist in locating the coordinates of the potential danger behavior, and plan and generate a second flight path based on the inspection area, the photovoltaic panel coordinates, and the coordinates of the potential danger behavior; The drone is equipped with a detection device and moves to the location of the potential danger behavior, and uses the detection device to determine whether there is a potential danger at the location of the potential danger behavior; The detection device includes a mobile camera; The hidden dangers include: animals digging holes or geological changes causing holes to be washed away by rainwater, resulting in a depression in the land where the busbar wires are exposed, and an opening forming at the top of the depression; When a hidden danger is confirmed, the drone dumps paint to mark the hidden danger and uploads the coordinates of the confirmed hidden danger; Taking an image with the mobile camera according to the coordinates of the potential danger behavior location, pixelating the image, and using a scale to determine the size of the image using the flight altitude and the pixels of the image, thereby determining the opening perimeter of the potential danger behavior location; The drone dumps paint markings according to the opening perimeter of the hidden danger behavior location.

2. The factory intelligent operation and maintenance inspection method according to claim 1, characterized in that: Mark the coordinates where the busbar cable coincides with the location of the potential danger behavior; A cable pre-buried threshold is set, and when the detection device detects that the land depth data of the coincident coordinates is greater than or equal to the cable pre-buried threshold, it is determined that there is a hidden danger at the coordinates; The distance between the detection device and the ground is equal to the set flight altitude.

3. The factory intelligent operation and maintenance inspection method according to claim 1, characterized in that: Determine the inclination of rainwater according to wind direction and adjust the flight attitude of the drone in the rainwater; Adjust the angle of the detection equipment according to the inclination of the rain and plan a path close to the potential danger behavior.

4. The factory intelligent operation and maintenance inspection method according to claim 3 is characterized by: The detection equipment also includes an ultrasonic sensor, a laser sensor, a Hall effect sensor and a temperature sensor; The mobile camera is used to capture images of land depressions; The ultrasonic sensor and laser sensor detect the depth data of land depression; The Hall effect sensor detects leakage data; The temperature sensor detects whether there is a severe fever.

5. The factory intelligent operation and maintenance inspection method according to claim 4 is characterized by: Also included are historical data, wherein the historical data includes coordinates of past maintenance locations; A maintenance frequency threshold is set, and when the previous maintenance position coordinates are greater than or equal to the maintenance frequency threshold, the previous maintenance position coordinates are selected, and auxiliary planning is performed based on the selected previous maintenance position coordinates to generate a second flight path.

6. The factory intelligent operation and maintenance inspection method according to claim 5, characterized in that: Adjust the dumping ratio according to the opening perimeter at the location of the hidden danger behavior; A paint dumping path is planned according to the coordinate digital image of the hidden danger behavior location, and the paint dumping path is the same as the coordinate digital image of the hidden danger behavior location.

7. The factory intelligent operation and maintenance inspection method according to claim 6, characterized in that: The second flight path includes a flight path and a detection path; The flight path includes the path between the current path point of the drone and the path point near the potential risk behavior; The detection path includes a path between a path point near a potential hazard behavior and a path point at the potential hazard behavior; Determine the coordinates of the potential danger behavior and the next flight path connected to it; The flight of the next flight path is used to blow away water droplets on the detection equipment.

8. The factory intelligent operation and maintenance inspection method according to claim 7, characterized in that: The pigment markers include three color markers: red, yellow and blue; Red paint marks indicate danger and require power outage for repairs; Yellow paint marks indicate doubts and require detailed inspection of potential hazards; Blue paint marks indicate safety and the area where the hazardous behavior is to be reburied.

9. An inspection system using the factory intelligent operation and maintenance inspection method according to claim 1, characterized in that: include: A generation module is configured to determine the coordinates of photovoltaic panels and busbar cables of the photovoltaic power station and generate an inspection area, wherein the generation module determines a first flight path based on the inspection area; A shooting module is used to record the video of the photovoltaic panel and the bus cable in real time, and to determine the coordinates of the hidden danger behavior through the coordinates of the photovoltaic panel and the bus cable; A detection module, which determines whether there is a hidden danger at the hidden danger behavior location through the detection module, and modifies the first flight path to generate a second flight path based on the detected danger; A storage module, the storage module is used to store the video captured by the shooting module and historical maintenance data; The marking module stores three colors of pigments, and marks corresponding to different risks are created by pouring different colors of pigments.

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