Photovoltaic power station unmanned aerial vehicle inspection route determination method, device, equipment and medium

Abstract

The application relates to the new energy technology field and specifically provides a photovoltaic power station unmanned aerial vehicle inspection route determination method, device, equipment and medium, the method comprises the following steps: acquiring inspection task information, constructing an initial inspection route of a target inspection area based on the inspection task information; determining a solar incident vector of each reference waypoint timestamp of the initial inspection route and a photovoltaic panel normal vector of the target inspection area at each reference waypoint timestamp; calculating a glare reflection vector of each reference waypoint timestamp, and then determining a safety offset vector for each reference waypoint; based on the safety offset vector of each reference waypoint, a preset safety offset distance is applied to each reference waypoint respectively, a plurality of first offset waypoints are obtained, and finally, the final inspection route is obtained by fitting the first offset waypoints. The application effectively solves the image oversaturation exposure problem caused by photovoltaic panel mirror reflection when the unmanned aerial vehicle inspects the tracking type photovoltaic power station, and ensures the accuracy and reliability of the inspection result.

Description

Technical Field

[0001] This application relates to the field of new energy technology, and in particular to a method, device, equipment and medium for determining the inspection route of a photovoltaic power station by a drone. Background Technology

[0002] As a crucial force driving energy structure transformation, the long-term, stable, and efficient operation of photovoltaic (PV) power plants is essential for ensuring energy supply. Using drones equipped with thermal imaging devices to inspect PV power plants is a common technique for detecting potential faults such as "hot spots." However, during inspections, glare caused by sunlight reflecting off the specular surfaces of PV panels can lead to localized oversaturation in thermal imaging images, obscuring the true hot spot information and affecting the accuracy of inspection results. Therefore, effectively avoiding glare during inspections is a pressing technical problem. To address this issue, a glare avoidance method based on inspection time window planning is proposed. This method first obtains the geographical coordinates of the PV power plant and the inherent tilt angle of the PV panels. Then, the system establishes a solar trajectory model, accurately calculating the sun's angle for every day and every moment of the year. Finally, by substituting the camera's field of view, the fixed tilt angle of the PV panels, and the real-time sun angle into preset geometrical-optical constraints, a time interval within the day free from specular reflection is selected and provided as a recommended safe time window for maintenance personnel to conduct inspections within this period.

[0003] Currently, to maximize power generation efficiency, new photovoltaic power plants widely use tracking photovoltaic (PV) brackets that can track the sun's position in real time, and the attitude of the PV panels changes dynamically over time. Related technologies calculate the safe time window based on the premise that the PV panel tilt angle is fixed. Therefore, when this method is applied to tracking PV power plants, the static tilt angle used for calculation does not match the real-time attitude of the PV panels. This causes the drone to still encounter specular reflections when inspecting along its flight path within the window, resulting in oversaturated exposure of the acquired images and affecting the accuracy and reliability of the drone inspection results. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method, apparatus, equipment, and medium for determining the inspection route of a photovoltaic power station using a drone. This method avoids oversaturation exposure of images caused by specular reflection from photovoltaic panels when a drone inspects a tracking photovoltaic power station, thereby ensuring the accuracy and reliability of the drone inspection results.

[0005] To achieve the objectives of this application, the following technical solution is provided: Firstly, this application provides a method for determining the unmanned aerial vehicle (UAV) inspection route for photovoltaic power plants, including: Obtain inspection task information and construct an initial inspection route for the target inspection area based on the inspection task information; Determine the solar incidence vector of each reference waypoint timestamp of the initial inspection route and the photovoltaic panel normal vector of the photovoltaic panel in the target inspection area at each reference waypoint timestamp; Glare reflection vectors for each reference waypoint timestamp are generated based on the solar incident vector and the photovoltaic panel normal vector. Then, for each reference waypoint, the cross product of the glare reflection vector and the photovoltaic panel normal vector is calculated to obtain the safety offset vector for each reference waypoint. The safety offset vector is perpendicular to the glare reflection vector and perpendicular to the photovoltaic panel normal vector. Based on the safety offset vector of each reference waypoint, a preset safety offset distance is applied to each reference waypoint to obtain multiple first offset waypoints, and then each first offset waypoint is fitted to obtain the final inspection route.

[0006] By adopting the above technical solution, an initial inspection route with timestamps is first constructed based on the inspection task information. The normal vector of the photovoltaic panel at each reference waypoint during the inspection process is accurately predicted. Then, by calculating the solar incident vector and the normal vector of the photovoltaic panel, the reflection direction of glare is predicted, and the glare reflection vector is obtained. By calculating the cross product of the glare reflection vector and the normal vector of the photovoltaic panel, a safety offset vector perpendicular to both is obtained. This safety offset vector provides a geometrically optimal offset direction for the UAV to avoid glare, so that the route planning system offsets the reference waypoints along this direction, ensuring that the UAV escapes the path of glare reflection while maintaining effective observation of the photovoltaic panel. Thus, a final inspection route that effectively avoids glare is planned, effectively solving the problem of image oversaturation exposure caused by specular reflection of photovoltaic panels when the UAV inspects a tracking photovoltaic power station. This ensures the accuracy of the UAV inspection results and significantly improves the scientific nature of the inspection route planning and the reliability of the inspection results.

[0007] A further improvement of this invention is that the construction of the initial inspection route for the target inspection area based on the inspection task information includes: obtaining the photovoltaic array layout information of the target inspection area; dividing the target inspection area into multiple target photovoltaic array areas based on the photovoltaic array layout information, and determining the geometric center point of each target photovoltaic array area as a reference waypoint; sorting the multiple reference waypoints to generate an ordered path with the shortest total flight distance, and calculating the flight time between each two adjacent reference waypoints on the ordered path based on a preset UAV flight speed; accumulating all flight times on the ordered path starting from the inspection start time, and assigning a unique timestamp to each reference waypoint to obtain the initial inspection route.

[0008] By adopting the above technical solution, and by acquiring photovoltaic array layout information and dividing it into multiple target photovoltaic array regions on an even basis, the integrity and uniformity of the inspection coverage are ensured. The geometric center point of each target photovoltaic array region is determined as the reference waypoint, and the shortest path algorithm is used to sort them, thus optimizing the flight distance. By combining the preset UAV flight speed to calculate the flight time between adjacent reference waypoints, and accumulating and allocating the time starting from the inspection start time, the flight planning system establishes a precise spatiotemporal correspondence for each reference waypoint. Therefore, this initial flight path construction method based on geometric optimization and precise time allocation provides a basic flight path for subsequent glare avoidance optimization, ensuring the efficiency of the inspection task.

[0009] A further improvement of the present invention is that determining the solar incidence vector of each reference waypoint timestamp of the initial inspection route and the photovoltaic panel normal vector of the photovoltaic panel in the target inspection area at each reference waypoint timestamp includes: determining the inspection duration based on the initial inspection route, and then calculating the solar trajectory information during the operation of the initial inspection route by combining the position coordinates in the inspection task information; the solar trajectory information includes data on the changes of the solar altitude angle and solar azimuth angle over time within the inspection duration; calculating the solar incidence at each reference waypoint timestamp based on the initial inspection route and the solar trajectory information to obtain the solar incidence vector at each reference waypoint timestamp; obtaining the control parameters of the photovoltaic support in the target inspection area, and then determining the photovoltaic panel normal vector at each reference waypoint timestamp based on the solar trajectory information; the control parameters include the spatial attitude of the support rotation axis, the rotation angle range, and the rotation control strategy.

[0010] In this way, based on the spatiotemporal correspondence of the reference waypoints of the initial inspection route, the solar incidence vector is calculated by combining the solar trajectory information. At the same time, based on the established photovoltaic panel attitude prediction system, after obtaining the control parameters of the photovoltaic support, the real-time normal vector of the photovoltaic panel at each moment can be accurately predicted, breaking through the limitation of fixed tilt angle of photovoltaic panels in traditional methods.

[0011] A further improvement of the present invention is that the step of obtaining the control parameters of the photovoltaic support within the target inspection area, and then determining the photovoltaic panel normal vector for each reference waypoint's corresponding timestamp based on the solar trajectory information, includes: determining the solar altitude angle and solar azimuth angle for each reference waypoint's corresponding timestamp based on the solar trajectory information; calculating the target rotation angle of the photovoltaic support at each timestamp based on the solar altitude angle, the solar azimuth angle, and the rotation control strategy; establishing a spatial coordinate transformation matrix for the photovoltaic panel's attitude based on the spatial attitude of the support's rotation axis and the target rotation angle; obtaining the initial normal vector of the photovoltaic panel at the start of the inspection, and substituting the initial normal vector into the spatial coordinate transformation matrix to obtain the photovoltaic panel normal vector corresponding to each timestamp.

[0012] Here, by acquiring the control parameters of the photovoltaic support and combining them with solar trajectory information to calculate the solar altitude angle and azimuth angle at each time stamp, the flight path planning system can accurately predict the target rotation angle of the photovoltaic support at any given time. Based on the spatial attitude of the support's rotation axis and the target rotation angle, a spatial coordinate transformation matrix is ​​established. Substituting the initial normal vector at the start of the inspection into this spatial coordinate transformation matrix, the flight path planning system can track the dynamic changes of the photovoltaic panel's normal vector in real time, ensuring the accuracy of the attitude calculation for the tracking photovoltaic support.

[0013] A further improvement of the present invention is that, after applying a preset safety offset distance to each reference waypoint based on the safety offset vector of each reference waypoint to obtain multiple first offset waypoints, the invention further includes: determining the line-of-sight vector of the UAV camera at each of the first offset waypoints, wherein the line-of-sight vector is the geometric center pointing from the first offset waypoint to the corresponding target photovoltaic array area; and calculating the inspection tilt angle and glare avoidance angle for each of the first offset waypoints based on the line-of-sight vector, wherein the inspection tilt angle is the angle between the line-of-sight vector and the corresponding normal vector of the photovoltaic panel, and the glare avoidance angle is... The angle between the line-of-sight vector and the corresponding glare reflection vector; determining whether the inspection tilt angle and the glare avoidance angle of each first offset waypoint meet preset waypoint quality conditions; the waypoint quality conditions include: the inspection tilt angle is less than a preset tilt angle upper limit threshold, and the glare avoidance angle is greater than a preset avoidance threshold; if the inspection tilt angle or the glare avoidance angle does not meet the preset waypoint quality conditions, adjusting the target offset waypoint that does not meet the waypoint quality conditions until the adjusted target offset waypoint meets the waypoint quality conditions, and determining the second offset waypoint.

[0014] In this way, after generating the offset waypoints, the quality of the waypoints is checked and optimized in a closed loop. The flight path planning system constructs the line-of-sight vector of the UAV camera and calculates two core indicators based on this: the inspection tilt angle and the glare avoidance angle. This allows for a quantitative evaluation of the effectiveness of the offset waypoints. The inspection tilt angle ensures that the imaging angle is not too large, which could lead to image distortion or information loss, while the glare avoidance angle ensures a safe distance from the glare path. When either indicator fails to meet the preset conditions, the flight path planning system initiates an adjustment procedure to ensure that each waypoint on the final flight path not only successfully avoids glare but also guarantees high-quality inspection imaging. This achieves an effective balance between avoiding glare and ensuring inspection quality, improving the practicality of the inspection flight path planning while ensuring the accuracy of the UAV inspection results.

[0015] A further improvement of the present invention is that, when the inspection tilt angle or the glare avoidance angle does not meet the preset waypoint quality conditions, adjusting the target offset waypoint that does not meet the waypoint quality conditions until the adjusted target offset waypoint meets the waypoint quality conditions, and determining the second offset waypoint, includes: calculating the avoidance angle difference between the glare avoidance angle corresponding to the target offset waypoint and the avoidance threshold; determining a safe offset adjustment amount based on the avoidance angle difference, and accumulating the safe offset adjustment amount with the current safe offset distance to obtain a new safe offset distance; determining the adjusted target offset waypoint based on the new safe offset distance and the safe offset vector corresponding to the reference waypoint, and recalculating the line-of-sight vector, the inspection tilt angle, and the glare avoidance angle based on the adjusted target offset waypoint; and determining the adjusted target offset waypoint as the second offset waypoint when the adjusted target offset waypoint meets the waypoint quality conditions.

[0016] In this way, by calculating the difference between the glare avoidance angle and the avoidance threshold, the route planning system can quantify the gap between the waypoint deviation and the safety requirements. Subsequently, based on this glare avoidance angle difference, a safe deviation adjustment is determined and added to the current safe deviation distance to obtain a new safe deviation distance. This precise calculation method based on angle differences ensures the accuracy and relevance of the adjustment, avoiding over- or under-deviation issues. Therefore, through this quantitative adjustment mechanism, the route planning system can quickly converge to the optimal waypoint position that meets the quality conditions, significantly improving the efficiency and accuracy of route optimization.

[0017] A further improvement of the present invention is that, if the number of adjustments to a target offset waypoint that does not meet the waypoint quality conditions reaches a preset upper limit and the waypoint quality conditions are still not met, a target reference waypoint corresponding to the target offset waypoint is determined, and the timestamp of the target reference waypoint is adjusted; based on the adjusted timestamp, a new third offset waypoint is determined, and the line-of-sight vector, the inspection tilt angle, and the glare avoidance angle based on the third offset waypoint are recalculated, and the first third offset waypoint that meets the waypoint quality conditions is determined as the final second offset waypoint.

[0018] Thus, when the number of waypoint adjustments reaches a preset limit and still fails to meet the waypoint quality requirements, the route planning system shifts its optimization from the spatial dimension to the temporal dimension. By adjusting the timestamp of the baseline waypoint, it leverages the time-varying characteristics of the photovoltaic panel attitude and the sun's position to find more favorable observation conditions at different times. Based on the adjusted timestamp, the waypoint is redefined and relevant parameters are calculated. This allows the route planning system to overcome the limitations of simple spatial adjustments, ensuring that even in complex glare environments, a final waypoint meeting the quality requirements can be found. This significantly improves the success rate and adaptability of route planning, establishing a temporal and spatial optimization strategy for waypoints.

[0019] A further improvement of the present invention is that the step of determining the target reference waypoint corresponding to the target offset waypoint and adjusting the timestamp of the target reference waypoint includes: establishing a time adjustment window centered on the timestamp corresponding to the target reference waypoint in the initial inspection route; within the time adjustment window, searching forward or backward with a preset time step to generate one or more candidate timestamps; calculating the vector angle between the glare reflection vector and the photovoltaic panel normal vector corresponding to each candidate timestamp, and determining the candidate timestamp with the largest vector angle as the adjusted timestamp.

[0020] In this way, a time adjustment window is established centered on the original timestamp of the reference waypoint, and a systematic search is performed within this time adjustment window with a preset time step, ensuring the comprehensiveness and accuracy of time optimization. The route planning system calculates the vector angle between the glare reflection vector corresponding to each candidate timestamp and the normal vector of the photovoltaic panel, and selects the time point with the largest vector angle as the optimal adjustment time, realizing a time optimization strategy based on physical principles. This angle-optimized time selection mechanism ensures that the adjusted timestamp can provide accurate observation geometry conditions, effectively guaranteeing the glare avoidance effect.

[0021] Secondly, this application provides a device for determining the unmanned aerial vehicle (UAV) inspection route for a photovoltaic power station, comprising: The acquisition module is used to acquire inspection task information and construct an initial inspection route for the target inspection area based on the inspection task information. The first determining module is used to determine the solar incidence vector of each reference waypoint timestamp of the initial inspection route and the photovoltaic panel normal vector of the photovoltaic panel in the target inspection area at each reference waypoint timestamp. The second determining module is used to generate a glare reflection vector for each of the reference waypoint timestamps based on the solar incident vector and the photovoltaic panel normal vector, and then calculate the vector cross product of the glare reflection vector and the photovoltaic panel normal vector for each reference waypoint to obtain a safety offset vector for each reference waypoint; wherein, the safety offset vector is perpendicular to the glare reflection vector and the safety offset vector is perpendicular to the photovoltaic panel normal vector. The offset fitting module is used to apply a preset safe offset distance to each reference waypoint based on the safe offset vector of each reference waypoint to obtain multiple first offset waypoints, and then fit each of the first offset waypoints to obtain the final inspection route.

[0022] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the method for determining the unmanned aerial vehicle (UAV) inspection route for a photovoltaic power station as described above.

[0023] Fourthly, this application provides a computer-readable storage medium including instructions that, when executed on a flight path planning system, cause the flight path planning system to perform the photovoltaic power station UAV inspection flight path determination method as described above.

[0024] Compared with the prior art, the present invention has the following beneficial effects: The method, apparatus, equipment, and medium for determining the inspection route of photovoltaic power plants by UAV provided in this application employ dynamic glare reflection vector calculation technology based on the control parameters of the tracking photovoltaic support and safety offset vector generation technology based on cross product operation. This can accurately predict the actual attitude and glare reflection direction of the photovoltaic panel at each moment during the inspection process and provide the UAV with the geometrically optimal avoidance offset direction. This effectively solves the problem of glare avoidance failure of tracking photovoltaic power plants caused by the assumption of fixed tilt angle of photovoltaic panels in related technologies, and thus realizes accurate route planning in dynamic glare environment. Attached Figure Description

[0025] The accompanying drawings are provided to further understand this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. Figure 1 This is a schematic diagram of a photovoltaic power station drone inspection scenario provided in an embodiment of this application; Figure 2A schematic diagram of an optional method for determining the unmanned aerial vehicle (UAV) inspection route for a photovoltaic power station provided in an embodiment of this application; Figure 3 A schematic diagram of an optional method for determining the unmanned aerial vehicle (UAV) inspection route for a photovoltaic power station provided in an embodiment of this application; Figure 4 A schematic diagram of an optional method for determining the unmanned aerial vehicle (UAV) inspection route for a photovoltaic power station provided in an embodiment of this application; Figure 5 This is a schematic diagram of the physical device structure of the route planning system provided in the embodiments of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] 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 number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature; in the description of this application, unless otherwise stated, "multiple" means two or more.

[0028] Figure 1 This is a schematic diagram of a photovoltaic power station drone inspection scenario provided in an embodiment of this application, with reference to... Figure 1 As shown, the photovoltaic array 100 consists of multiple photovoltaic panels 102 mounted on photovoltaic brackets 101. To maximize power generation efficiency, the photovoltaic brackets 101 in this scenario are tracking brackets, and their attitude changes in real time with the position of the sun 120. During the inspection mission, the drone 110, equipped with a thermal imaging camera, needs to inspect the photovoltaic array 100 along a preset route to detect faults such as "hot spots." In the figure, the incident sunlight emitted by the sun 120 shines on the photovoltaic panels 102, producing glare reflections. Glare refers to the reflected light formed after sunlight is reflected by the mirror surface of the photovoltaic panel. When this reflected light enters the field of view of the drone's thermal imaging camera, it causes local oversaturation exposure of the image sensor, resulting in high-brightness areas in the thermal imaging image, which obscure the true temperature information and potential hot spot fault characteristics.

[0029] In related technologies, an inspection planning method based on a fixed safety time window can be adopted. Specifically, combined with... Figure 1In the scenario shown, traditional methods calculate a 24-hour effective safety inspection window based on the geographical location of the photovoltaic power station and a fixed tilt angle of the photovoltaic panels. This guides the drone 110 to take pictures along a conventional path directly above the geometric center of the photovoltaic array 100 within this inspection window. However, when facing the tracking photovoltaic support 101, the normal vector of the photovoltaic panel 102 changes in real time. When the drone 110 performs the planned shooting task, the attitude of the photovoltaic panel 102 may have already been adjusted, causing glare reflections to enter the camera's field of view, resulting in localized overexposure of the image and making it impossible to effectively identify potential fault points on the photovoltaic panel 102.

[0030] To address the aforementioned technical problems, the present invention proposes the following technical solutions and corresponding embodiments.

[0031] The following is combined Figures 2 to 5 The illustrated embodiments describe the technical solution of the present invention: Example 1 Figure 2 This is a flowchart illustrating a method for determining the unmanned aerial vehicle (UAV) inspection route for a photovoltaic power station, as described in this application. Figure 2 As shown, the method for determining the unmanned aerial vehicle (UAV) inspection route of a photovoltaic power station according to an embodiment of this application includes the following steps S101 to S104: Step S101: Obtain inspection task information and construct an initial inspection route for the target inspection area based on the inspection task information.

[0032] In this embodiment, the inspection task information refers to a set of information related to the inspection pre-set by staff or the photovoltaic power station operation and maintenance management system before the UAV performs the inspection task, used to guide subsequent route planning; the target inspection area represents a specific area of ​​the photovoltaic power station that needs to be inspected by the UAV. In this embodiment, the initial inspection route is a route composed of multiple reference waypoints with timestamps, representing the initial flight path of the UAV without considering glare avoidance. The reference waypoints are spatial locations where the UAV needs to stop and take pictures during the inspection; the timestamps represent the estimated time when the UAV arrives at a certain reference waypoint. As an example, the initial inspection route can be a path connecting the geometric centers of multiple photovoltaic array areas, and the reference waypoints can be spatial locations located 30 meters directly above each photovoltaic array area.

[0033] In this embodiment, before planning the UAV inspection route, the route planning system first needs to obtain the basic information of the inspection task. Specifically, the route planning system obtains the inspection task information pre-set by the staff by interacting with the photovoltaic power station operation and maintenance management system. This inspection task information includes at least the three-dimensional spatial coordinates (position coordinates) of the area to be inspected, used to determine the spatial range of the UAV inspection; it also includes the specific time point at which the inspection begins (inspection start time), used to subsequently calculate the attitude changes of the photovoltaic panels at different times based on the solar trajectory. The route planning system verifies the validity of the obtained information to ensure that the coordinates are within the boundary of the photovoltaic power station and that the inspection time is within the valid working period.

[0034] In this embodiment, after obtaining the inspection task information, the route planning system needs to plan an initial route covering the entire target area. The route planning system first divides the target inspection area into several equal-sized sub-regions and uses the position above the geometric center of each sub-region as a reference waypoint. Then, the route planning system uses a shortest path algorithm to connect these reference waypoints into a path with the shortest total flight distance. Next, based on the UAV's preset flight speed (e.g., 5 m / s) and the distance between each reference waypoint, the route planning system calculates the time required for the UAV to fly from one reference waypoint to the next. Finally, using the inspection start time as a reference, the route planning system accumulates the flight time onto each reference waypoint and assigns a precise timestamp to each reference waypoint, thus obtaining a complete initial inspection route.

[0035] As one possible implementation method, refer to Figure 3 As shown, the initial inspection route for the target inspection area can be planned and constructed through the following steps S1011 to S1014: Step S1011: Obtain the photovoltaic array layout information of the target inspection area.

[0036] In this embodiment of the application, photovoltaic array layout information refers to a set of data describing the spatial distribution of photovoltaic panels within a photovoltaic power station, including the location, size, and arrangement of the photovoltaic array.

[0037] Step S1012: Based on the photovoltaic array layout information, the target inspection area is divided into multiple target photovoltaic array areas, and the geometric center point of each target photovoltaic array area is determined as the reference waypoint.

[0038] In this embodiment, the target photovoltaic array area is a sub-region unit to be inspected, obtained by dividing the target inspection area based on the position, size, and arrangement of the photovoltaic array. As a feasible implementation, after obtaining the inspection task information, the flight path planning system needs to rationally partition the inspection area. Specifically, the flight path planning system first reads the photovoltaic array layout information of the target inspection area from the photovoltaic power station's structural database, including the precise coordinates, size parameters, and arrangement spacing of each photovoltaic array. Then, based on the UAV camera's field of view and the desired image resolution, the flight path planning system calculates the optimal coverage area for a single shot. Next, using this area as a benchmark, the flight path planning system divides the entire inspection area into several equally sized rectangular sub-regions. The size of each sub-region must ensure that the UAV can complete a full shot of the area from a single waypoint.

[0039] As a feasible implementation method, the geometric center point of each target photovoltaic array region is determined as the reference waypoint. Here, the geometric center point refers to the spatial center position of the target photovoltaic array region; the reference waypoint represents the initial position point where the UAV needs to hover and take pictures.

[0040] Step S1013: Sort the multiple reference waypoints to generate an ordered path with the shortest total flight distance, and calculate the flight time between each pair of adjacent reference waypoints on the ordered path based on the preset UAV flight speed.

[0041] In this embodiment, an ordered path refers to the shortest flight route connecting all reference waypoints. In this embodiment, after completing the area division, the route planning system needs to plan an efficient inspection path. Specifically, the route planning system first calculates the geometric center coordinates of each target photovoltaic array area and sets a reference waypoint at a preset altitude directly above this center point. Then, the route planning system uses an improved shortest path algorithm (such as ant colony optimization or genetic algorithm) to solve for the shortest Hamiltonian cycle, obtaining a closed ordered path with the shortest total flight distance connecting all reference waypoints.

[0042] In this embodiment, after obtaining the shortest path, the route planning system needs to allocate time for each flight segment. Specifically, the route planning system first sets a suitable cruising speed based on the UAV's performance parameters and safety requirements; then, the route planning system sequentially calculates the three-dimensional Euclidean distances between adjacent waypoints in the ordered path; next, the route planning system divides these distances by the preset flight speed to obtain the theoretical flight time between each pair of adjacent waypoints; finally, the route planning system considers the UAV's acceleration and deceleration characteristics and corrects the theoretical flight time to obtain the actual flight time.

[0043] Step S1014: Starting from the inspection start time, accumulate all flight times on the ordered path and assign a unique timestamp to each reference waypoint to obtain the initial inspection route.

[0044] In this embodiment, after calculating the flight time for each segment, the route planning system needs to mark the specific arrival time for each reference waypoint. Specifically, the route planning system first sets the timestamp of the first reference waypoint as the inspection start time; then, following the ordered path, the route planning system sequentially adds the flight time of each segment to the timestamp of the previous waypoint to obtain the timestamp of the next waypoint. When accumulating the time, the route planning system also considers the hovering time (e.g., 5 seconds) required to perform the shooting task at each waypoint, including it in the time calculation. Finally, the route planning system obtains a complete initial inspection route, where each reference waypoint is clearly marked with a timestamp.

[0045] Step S102: Determine the solar incidence vector of each reference waypoint timestamp of the initial inspection route and the photovoltaic panel normal vector of the photovoltaic panel in the target inspection area at each reference waypoint timestamp.

[0046] In this embodiment, the inspection duration is determined based on the initial inspection route. Then, the solar trajectory information during the operation of the initial inspection route is calculated by combining the position coordinates in the inspection task information. The solar trajectory information includes data on the changes of the solar altitude angle and solar azimuth angle over time within the inspection duration. Based on the initial inspection route and solar trajectory information, the solar incidence at the timestamp corresponding to each reference waypoint is calculated to obtain the solar incidence vector at each reference waypoint timestamp. The control parameters of the photovoltaic support within the target inspection area are obtained, and then the photovoltaic panel normal vector at the timestamp corresponding to each reference waypoint is determined based on the solar trajectory information. The control parameters include the spatial attitude of the support rotation axis, the rotation angle range, and the rotation control strategy.

[0047] In this embodiment, the inspection duration represents the total time required to complete the entire inspection task; solar trajectory information refers to a data set describing the changes in the sun's position in the sky; solar altitude angle represents the angle between the sun and the ground plane; solar azimuth angle refers to the angle between the sun's projection onto the ground plane and true north; solar incident vector refers to a vector representing the direction of sunlight illuminating the photovoltaic panel surface, with its direction pointing from the sun to the photovoltaic panel surface. For example, the solar altitude angle at a certain moment might be 45 degrees, and the azimuth angle might be 30 degrees east of south.

[0048] After completing the initial flight path planning, the flight path planning system needs to calculate the sun's positional changes throughout the entire inspection process. Specifically, the system first subtracts the inspection start time from the timestamp of the last reference waypoint to obtain the total time required to complete the entire inspection task. Then, the system substitutes the geographical coordinates of the target inspection area into relevant astronomical calculation models (such as the formula for calculating the sun's position) to calculate the sun's spatial angle at any given time. The system samples the entire inspection duration at preset time intervals (e.g., 1 minute), calculating the corresponding solar altitude angle and solar azimuth angle for each sampled time, ultimately generating a complete solar trajectory dataset. This preset time interval is at least less than the difference in timestamps between the reference waypoints.

[0049] After obtaining the solar trajectory information, the flight path planning system needs to convert the solar angle information into a vector representation in three-dimensional space. Specifically, the system first extracts the timestamp of each reference waypoint from the initial inspection route, and then finds the solar altitude angle and solar azimuth angle corresponding to each timestamp based on the solar trajectory information. Next, the system establishes a three-dimensional Cartesian coordinate system with the center of the target inspection area as the origin, converting the solar altitude angle and solar azimuth angle into direction vectors in three-dimensional space. Then, using the conversion formula from spherical coordinates to Cartesian coordinates, the system converts the solar altitude angle and solar azimuth angle into a three-dimensional vector of unit length. The solar altitude angle determines the angle between the vector and the horizontal plane, and the solar azimuth angle determines the angle between the projection of the vector onto the horizontal plane and the due south direction. Finally, the system obtains the solar incidence vector at the corresponding timestamp for each reference waypoint, which accurately describes the direction in which sunlight shines on the photovoltaic panel at that moment.

[0050] In this embodiment, the control parameters of the photovoltaic support refer to a set of technical parameters describing the motion characteristics of the tracking support, including the spatial attitude of the support's rotation axis, the range of rotation angles, and the rotation control strategy; the photovoltaic panel normal vector represents the unit vector in the vertical direction of the photovoltaic panel surface; the spatial attitude of the rotation axis refers to the direction of the support's rotation axis in three-dimensional space; and the rotation control strategy indicates how the support adjusts its rotation angle according to the sun's position.

[0051] In this embodiment, after calculating the solar incident vector, the flight path planning system needs to determine the actual orientation of the photovoltaic panel at each moment. Specifically, the flight path planning system first obtains the control parameters of the photovoltaic support within the target area from the equipment parameter library of the photovoltaic power station. Then, based on the rotation control strategy of the photovoltaic support (such as single-axis tracking or dual-axis tracking), the flight path planning system calculates the optimal rotation angle that the photovoltaic support should take at the solar position corresponding to each reference waypoint timestamp. Next, the flight path planning system establishes a spatial coordinate transformation matrix, which contains the spatial direction and rotation angle information of the support's rotation axis. Finally, the flight path planning system substitutes the initial normal vector of the photovoltaic panel (determined by the photovoltaic panel's attitude at the start of the inspection, usually vertically upward) into the spatial coordinate transformation matrix to calculate the actual normal vector direction of the photovoltaic panel at each moment.

[0052] Step S103: Generate a glare reflection vector for each reference waypoint timestamp based on the solar incident vector and the photovoltaic panel normal vector. Then, for each reference waypoint, calculate the cross product of the glare reflection vector and the photovoltaic panel normal vector to obtain a safety offset vector for each reference waypoint. The safety offset vector is perpendicular to the glare reflection vector and the safety offset vector is perpendicular to the photovoltaic panel normal vector.

[0053] In this embodiment, the glare reflection vector refers to the unit vector of the propagation direction of sunlight after reflection from the photovoltaic panel surface, following the law of reflection. After determining the orientation of the photovoltaic panel at various times, the flight path planning system needs to calculate the direction of reflected light rays that may affect the imaging of the UAV camera. Specifically, the flight path planning system applies the law of reflection, that is, the angle of incidence equals the angle of reflection, and the incident ray, reflected ray, and normal lie in the same plane. The flight path planning system first calculates the projection of the solar incident vector onto the normal vector of the photovoltaic panel, and then uses the vector form of the law of reflection: reflection vector = incident vector - 2 × (incident vector · normal vector) × normal vector, where "·" represents the vector dot product operation. In this way, the flight path planning system can obtain the glare reflection vector corresponding to each reference waypoint timestamp.

[0054] In this embodiment, the vector cross product refers to the cross product operation between the glare reflection vector and the photovoltaic panel normal vector, the result of which is a new vector perpendicular to both vectors. In this embodiment, after calculating the glare reflection vector at each reference waypoint, the flight path planning system needs to determine the safe offset direction of the UAV. Specifically, the flight path planning system first performs a cross product operation on the glare reflection vector and the photovoltaic panel normal vector corresponding to each reference waypoint. Since the geometric meaning of the cross product operation is to obtain a new vector perpendicular to both input vectors, the result points to a spatial direction that avoids reflected light without excessively deviating from the observation direction. Next, the flight path planning system normalizes the vector obtained from the cross product, that is, adjusts the length of the vector to 1, obtaining a safe offset vector of unit length. Here, the safe offset vector is perpendicular to both the glare reflection vector and the photovoltaic panel normal vector.

[0055] Step S104: Based on the safety offset vector of each reference waypoint, apply a preset safety offset distance to each reference waypoint to obtain multiple first offset waypoints, and then fit each first offset waypoint to obtain the final inspection route.

[0056] In the embodiments of this application, the safe offset distance refers to the spatial distance that the UAV needs to offset from the reference waypoint; the offset waypoint represents the new waypoint position obtained after adjustment by the safe offset vector and the safe offset distance; the final inspection route refers to the actual flight path formed by connecting all the offset waypoints; and waypoint fitting refers to connecting discrete waypoints into a smooth curve using mathematical methods.

[0057] In this embodiment, after obtaining the safety offset vectors of each reference waypoint, the route planning system needs to generate a practically executable inspection route. Specifically, the route planning system first determines a suitable safety offset distance based on the size of the photovoltaic panel, the UAV's camera parameters (such as field of view, focal length, etc.), and the desired imaging resolution. Then, the route planning system translates each reference waypoint along its corresponding safety offset vector by this distance to obtain a new offset waypoint. To ensure the smoothness and executability of the flight path, the route planning system uses a curve fitting algorithm to connect these discrete offset waypoints into a continuous and smooth curve. During the fitting process, the route planning system considers the UAV's kinematic constraints (such as minimum turning radius, maximum climb angle, etc.) to ensure that the generated route meets the UAV's flight capabilities. Finally, the route planning system outputs this final inspection route optimized for glare avoidance for use by the UAV when performing inspection tasks.

[0058] Here, the method for determining the inspection route of a photovoltaic power station by a drone in this application can be applied to the identification and early warning of fire hazards in photovoltaic power stations.

[0059] Therefore, referring to Figure 1The method for determining the inspection route of a photovoltaic power station using a UAV in this embodiment involves calculating the path of glare reflection light based on the timestamp, solar trajectory information, and photovoltaic support control parameters of the reference waypoint when planning the reference waypoint. Subsequently, the system calculates a safety offset vector to guide the UAV 110 to offset from the reference waypoint to an offset waypoint that effectively avoids glare reflection light for taking pictures. Inspection from the offset waypoint ensures effective observation of the photovoltaic panel 102 by the UAV without being affected by glare, thus obtaining high-quality inspection images. Connecting multiple such offset waypoints forms a safe and efficient final inspection route. This not only achieves dynamic glare avoidance in UAV inspection tasks but also effectively solves the problem of glare avoidance failure and poor inspection data quality caused by related technologies not considering the dynamic changes in the attitude of the tracking support, thereby improving the accuracy of UAV photovoltaic inspection.

[0060] The method for determining the inspection route of a photovoltaic power station using a drone provided in this embodiment, by adopting the above-mentioned technical solution, establishes the spatiotemporal correspondence of the reference waypoint by constructing an initial inspection route with a timestamp, and calculates the solar incidence vector by combining the solar trajectory information. After obtaining the control parameters of the photovoltaic support, the route planning system can accurately predict the real-time normal vector of the photovoltaic panel at each moment, breaking through the limitation of the fixed tilt angle of the photovoltaic panel in traditional methods. At the same time, the route planning system uses the law of reflection of light to calculate the glare reflection vector, and through the cross product operation with the normal vector of the photovoltaic panel, obtains an optimal offset direction that ensures that the drone stays away from the glare path without affecting the observation effect. The reference waypoint is offset along this direction and fitted to obtain the inspection route. This fundamentally solves the problem of glare avoidance failure caused by the dynamic change of the photovoltaic panel attitude in tracking photovoltaic power stations, significantly improves the scientificity and reliability of drone inspection, and ensures the accuracy of drone inspection results.

[0061] Example 2 Based on the above embodiments, this embodiment also provides a method for determining the inspection route of a photovoltaic power station using a drone, referring to... Figure 4 As shown, the method of this embodiment includes the following steps S201 to S226, which include the following contents: Step S201: Obtain preset inspection task information; In this embodiment of the application, the inspection task information includes the location coordinates of the target inspection area and the inspection start time. The location coordinates refer to the longitude, latitude, and altitude of the target inspection area in geographic space. Here, step S201 and Figure 2 The description of step 101 in the above embodiments is similar and will not be repeated here.

[0062] Step S202: Obtain the photovoltaic array layout information of the target inspection area, and divide the photovoltaic array layout information into multiple target photovoltaic array areas on an average basis; Step S203: Determine the geometric center point of each target photovoltaic array region as the reference waypoint, and sort the reference waypoints to obtain an ordered path with the shortest total flight distance; Step S204: Calculate the flight time of the UAV between adjacent reference waypoints on the ordered path based on the preset UAV flight speed; Step S205: Starting from the inspection start time, accumulate the flight time and assign a unique timestamp to each of the reference waypoints to obtain the initial inspection route. In this embodiment of the application, the content of steps S202 to S205 is the same as... Figure 3 The descriptions of steps S1011 to S1014 in the embodiments are similar and will not be repeated here. Please refer to the descriptions of the relevant steps.

[0063] Step S206: Determine the inspection duration based on the initial inspection route, and calculate the solar trajectory information in conjunction with the inspection task information; Here, the solar trajectory information includes data on the changes in the sun's altitude and azimuth angles over time during the inspection period; Step S207: Based on the initial inspection route and the solar trajectory information, calculate the solar incidence vector of each reference waypoint corresponding to the timestamp.

[0064] Here, steps S206 and S207 are... Figure 2 The description of step S102 in the above embodiments is similar and will not be repeated here. Please refer to the description of the relevant steps.

[0065] Step S208: Obtain the control parameters of the photovoltaic support within the target inspection area; The control parameters include the spatial attitude of the support rotation axis, the rotation angle range, and the rotation control strategy. In this embodiment, after obtaining the initial inspection route, the route planning system needs to understand the motion characteristics of the photovoltaic support to predict the real-time attitude of the photovoltaic panels during the inspection. Specifically, the route planning system first connects to the equipment management system of the photovoltaic power station to obtain the model information of the photovoltaic support installed in the target area. Then, the route planning system reads the detailed technical parameters of the support model from the equipment parameter database, including the installation direction of the rotation axis, the mechanical limit angle, and the control mode.

[0066] In cases where multiple bracket types exist within a given area, the flight path planning system establishes a parameter mapping table to record the specific bracket parameters corresponding to each target photovoltaic array region. These parameters will be used to subsequently calculate the spatial attitude of the photovoltaic panels at different times.

[0067] Step S209: Based on the solar trajectory information, calculate the solar altitude angle and solar azimuth angle of each reference waypoint corresponding to the timestamp; In this embodiment, after obtaining the photovoltaic support parameters, the flight path planning system needs to determine the sun's position at each inspection time. Specifically, the flight path planning system first extracts solar angle data covering the entire inspection period from the previously calculated solar trajectory information. Then, the flight path planning system interpolates the timestamp of each reference waypoint to obtain the precise solar altitude angle and azimuth angle at that moment. To improve calculation accuracy, the flight path planning system adopts a spherical astronomy algorithm, considering the influence of factors such as geographical latitude and atmospheric refraction on the sun's position, ensuring that the accuracy of the calculation results meets the requirements of photovoltaic support control.

[0068] Step S210: Based on the solar altitude angle and the solar azimuth angle, and in conjunction with the rotation control strategy, calculate the target rotation angle of the photovoltaic support at each time stamp; In the embodiments of this application, the target rotation angle refers to the optimal angle position that the photovoltaic support needs to be adjusted to at a specific moment; the rotation control strategy refers to the calculation method of converting the sun's position into the rotation angle of the support.

[0069] In this embodiment, after determining the sun's position at each moment, the flight path planning system needs to calculate the attitude the photovoltaic support should adopt. Specifically, the flight path planning system first selects the appropriate angle calculation model based on the support's rotation control strategy type (e.g., single-axis tracking or dual-axis tracking). For a single-axis tracking system, the flight path planning system projects the sun's azimuth angle onto a plane perpendicular to the rotation axis and calculates the optimal tracking angle; for a dual-axis tracking system, the flight path planning system considers both the elevation angle and azimuth angle simultaneously and calculates the target angles for both rotation axes. Then, the flight path planning system checks whether the calculated angle exceeds the mechanical limit range of the support; if it does, the angle is limited to the effective range. Finally, the flight path planning system rounds the angle to match the angle resolution of the support control system.

[0070] Step S211: Based on the spatial attitude of the support rotation axis and the target rotation angle, establish the spatial coordinate transformation matrix of the photovoltaic panel attitude; In this embodiment, the spatial coordinate transformation matrix refers to a mathematical matrix used to describe the spatial transformation relationship of the photovoltaic panel from its initial posture (such as the posture at the start of the inspection) to its target posture (the posture corresponding to the target rotation angle). Through this matrix, the vector under the initial posture can be converted into the vector under the target posture. For example, a 3×3 orthogonal matrix can realize rotation transformation in three-dimensional space; the photovoltaic panel posture represents the orientation state of the photovoltaic panel in space.

[0071] After calculating the target rotation angle of the photovoltaic (PV) support, the flight path planning system needs to establish a mathematical model to describe the spatial attitude change of the PV panel. Specifically, the system first establishes a local coordinate system with the PV support installation point as the origin, normalizing the direction of the support's rotation axis to a unit vector. Then, using the Rodriguez rotation formula or Euler angle transformation method, the system constructs a basic rotation matrix based on the rotation axis direction and the target rotation angle. For a dual-axis tracking system, the system needs to multiply the transformation matrices of the two rotation axes sequentially according to the installation order. Finally, the system expands the rotation matrix into a homogeneous transformation matrix, incorporating the PV panel's positional offset information relative to the support, to obtain a complete spatial coordinate transformation matrix. For example, when the target rotation angle is 45°, the system substitutes the rotation axis unit vector and 45° into the formula to calculate the corresponding 3×3 transformation matrix, which accurately reflects the PV panel's rotation process from its initial attitude to its target attitude.

[0072] Step S212: Obtain the initial normal vector of the photovoltaic panel at the start time of the inspection, and substitute the initial normal vector into the spatial coordinate transformation matrix to obtain the photovoltaic panel normal vector corresponding to each timestamp. In this embodiment, the initial normal vector refers to the vertical unit vector of the photovoltaic panel surface at the start of the inspection; the photovoltaic panel normal vector represents the vertical direction of the photovoltaic panel surface at any time. For example, if the photovoltaic panel is initially horizontal and facing upwards, its initial normal vector can be represented as (0, 0, 1). After coordinate transformation, the normal vector corresponding to a certain timestamp may become (0.866, 0, 0.5).

[0073] After establishing the spatial coordinate transformation matrix, the flight path planning system needs to calculate the real-time orientation of the photovoltaic panels during the inspection process. Specifically, the system first determines the initial normal vector of the photovoltaic panels based on their attitude at the start of the inspection. Then, it substitutes this initial normal vector into the spatial coordinate transformation matrix corresponding to each timestamp for calculation. The system normalizes the calculation results to ensure that the obtained direction vector is of unit length. Finally, the system stores the normal vectors of the photovoltaic panels corresponding to all timestamps in a vector array.

[0074] Therefore, by adopting the spatial coordinate transformation matrix establishment technology based on the photovoltaic support rotation control strategy and the accurate real-time calculation method of photovoltaic panel normal vector, it is possible to accurately simulate the spatial attitude change of the photovoltaic panel at any time according to the specific control mode and rotation parameters of the support, and accurately calculate the corresponding normal vector, thereby realizing the accurate calculation and prediction of the dynamic characteristics of tracking photovoltaic power station.

[0075] Step S213: Calculate the glare reflection vector of each reference waypoint corresponding to the timestamp based on the solar incident vector and the photovoltaic panel normal vector; Step S214: Calculate the cross product of the glare reflection vector and the photovoltaic panel normal vector to obtain the safety offset vector of each reference waypoint; The safety offset vector is perpendicular to both the glare reflection vector and the photovoltaic panel normal vector.

[0076] Here, steps S213 and S214 are... Figure 2 The description of S103 in the above embodiments is similar and will not be repeated here. Please refer to the description of the relevant steps.

[0077] Step S215: Apply a preset safety offset distance to the reference waypoint based on the safety offset vector to obtain multiple offset waypoints; In this embodiment, after calculating the safety offset vector, the flight path planning system needs to determine the actual inspection location. Specifically, the system first calculates a suitable safety offset distance based on the physical dimensions of the photovoltaic panel, the imaging parameters of the UAV camera (such as field of view and focal length), and the desired image resolution. Then, the system multiplies this offset distance by the safety offset vector corresponding to each reference waypoint to obtain the offset vector in three-dimensional space. Finally, the system superimposes this offset vector onto the coordinates of the reference waypoints to calculate the new offset waypoint positions. The system also checks whether these offset waypoints meet flight safety requirements, such as ensuring a minimum safe distance from the photovoltaic panel and avoiding collisions with other obstacles.

[0078] Step S216: Determine the line-of-sight vector of the UAV camera at each offset waypoint; based on the line-of-sight vector, calculate the inspection tilt angle and glare avoidance angle at each offset waypoint; Wherein, the line-of-sight vector is the geometric center of the target photovoltaic array region pointed from the offset waypoint; In this embodiment of the application, based on the line-of-sight vector, the inspection tilt angle and glare avoidance angle of each offset waypoint are calculated. The inspection tilt angle is the angle between the line-of-sight vector and the corresponding photovoltaic panel normal vector, and the glare avoidance angle is the angle between the line-of-sight vector and the corresponding glare reflection vector. Here, the line-of-sight vector refers to the direction vector from the UAV camera position to the observed target.

[0079] Step S217: Determine whether the inspection tilt angle and the glare avoidance angle meet the preset waypoint quality conditions; Among them, the waypoint quality conditions include that the inspection tilt angle is less than the preset tilt angle upper limit threshold and the glare avoidance angle is greater than the preset avoidance threshold. In this embodiment, the inspection tilt angle refers to the angle between the line-of-sight vector and the photovoltaic panel normal vector; the glare avoidance angle refers to the angle between the line-of-sight vector and the glare reflection vector; the tilt angle upper limit threshold refers to the maximum allowable observation tilt angle, used to ensure image quality; and the avoidance threshold refers to the minimum glare avoidance angle that must be maintained, used to avoid glare interference. For example, the tilt angle upper limit threshold may be set to 60 degrees, and the avoidance threshold may be set to 30 degrees.

[0080] In this embodiment, the flight path planning system determines the upper limit threshold for tilt angle based on the imaging quality requirements of the UAV camera. First, it acquires the camera's field of view, focal length, and target resolution parameters. Then, it calculates the degree of image distortion and the effective imaging area at different observation tilt angles. When the observation tilt angle exceeds a certain critical value, the image edge distortion will exceed the acceptable range, and the effective proportion of the photovoltaic panel in the image will be lower than the minimum coverage requirement. The flight path planning system uses this critical angle as the upper limit threshold for tilt angle.

[0081] Furthermore, the flight path planning system determines an avoidance threshold based on the degree of glare's impact on the imaging sensor. By analyzing the ratio of glare intensity to background signal at different angles, when the angle between the reflected glare and the line of sight is less than a certain value, the glare intensity will cause local oversaturation of the image, affecting the accuracy of hotspot recognition. The flight path planning system calculates the minimum safe angle required to ensure image quality as the avoidance threshold using historical experimental data.

[0082] After calculating the observation geometry, the route planning system needs to evaluate the availability of waypoint offsets. Specifically, the system compares the calculated inspection tilt angle with a preset upper limit threshold, and also compares the glare avoidance angle with a preset avoidance threshold.

[0083] Step S218: If yes, then the offset waypoint satisfies the waypoint quality condition; Step S219: If not, calculate the difference in avoidance angle between the glare avoidance angle corresponding to the offset waypoint and the avoidance threshold. Here, the waypoint that does not meet the quality conditions of the waypoint (the first waypoint) is defined as the waypoint that needs further adjustment.

[0084] Step S220: Determine the safety offset adjustment amount based on the avoidance angle difference, and add the safety offset adjustment amount to the current safety offset distance to obtain a new safety offset distance; Here, the safe offset adjustment amount refers to the additional offset distance required; the safe offset distance represents the spatial distance the UAV has deviated from the reference waypoint; the new safe offset distance refers to the total offset distance after adjustment. For example, if the current safe offset distance is 5 meters, and an adjustment of 2 meters is required based on the -10 degree avoidance angle difference, then the new safe offset distance is 7 meters.

[0085] After calculating the avoidance angle difference, the flight path planning system needs to convert the angle difference into a specific distance adjustment. Specifically, the system first calculates the minimum required position adjustment using trigonometric functions based on the avoidance angle difference and the current observation distance. Then, it multiplies this adjustment by a preset safety factor (e.g., 1.2) to ensure that the adjustment effectively avoids glare. Finally, the system adds the calculated adjustment to the current safe offset distance to obtain a new safe offset distance. If this new safe offset distance exceeds the preset maximum offset limit, causing the corresponding inspection tilt angle to exceed the preset tilt angle upper limit threshold, the system will truncate the new safe offset distance to within the allowable range.

[0086] In this embodiment, the flight path planning system determines a safety factor based on accumulated system errors and environmental uncertainties. First, it analyzes the distribution characteristics of various error sources, such as solar position calculation errors, photovoltaic panel attitude control accuracy errors, and UAV positioning accuracy errors. It then calculates the propagation impact of these errors in glare avoidance angle calculation, and further assesses the influence of environmental factors such as wind disturbances and atmospheric refraction on the actual observation geometry. The flight path planning system quantifies the combined impact of all error sources into a correction coefficient. This correction coefficient ensures that, after considering all uncertainties, the adjusted offset distance still reliably meets the glare avoidance requirements. The safety factor is set to 1 plus the combined error correction amount, typically ranging from 1.1 to 1.5.

[0087] Step S221: Based on the new safe offset distance and the safe offset vector corresponding to the reference waypoint, determine the adjusted offset waypoint, and recalculate the line-of-sight vector, the inspection tilt angle, and the glare avoidance angle so that the offset waypoint meets the waypoint quality conditions. Here, after determining the new offset distance, the route planning system needs to re-evaluate the adjusted observation effect. Specifically, the system multiplies the new safe offset distance by the original safe offset vector to calculate the new spatial offset. This offset is then added to the coordinates of the baseline waypoint to obtain the adjusted offset waypoint position. Simultaneously, the system recalculates the line-of-sight vector from this position to the center of the target area, and calculates the angle between this line-of-sight vector and the photovoltaic panel normal vector (inspection tilt angle) and the angle with the glare reflection vector (glare avoidance angle). The system compares these angles with preset thresholds to check if the waypoint quality conditions are met. If the adjusted waypoint meets the quality conditions, the adjusted offset waypoint (target offset waypoint) is designated as the new offset waypoint (second offset waypoint). If the conditions are still not met, and the maximum number of adjustments has not been reached, the system proceeds to the next round of adjustments.

[0088] Therefore, by using a dual quality assessment mechanism based on the line-of-sight vector and the inspection tilt angle and glare avoidance angle, as well as a closed-loop waypoint quality optimization and adjustment strategy, it is possible to ensure that the imaging quality is not affected while guaranteeing the glare avoidance effect. Through quantitative evaluation and iterative adjustment, it is ensured that each offset waypoint meets the preset quality conditions, effectively solving the problem in related technologies where simple glare avoidance may lead to excessive observation angles that affect image quality. Thus, an effective balance between glare avoidance and inspection quality is achieved.

[0089] Step S222: When the number of adjustments to the offset waypoint reaches the preset upper limit, if the offset waypoint still does not meet the waypoint quality conditions, a time adjustment window is established with the timestamp corresponding to the reference waypoint in the initial inspection route as the center. In this embodiment, after the number of location adjustments reaches a preset upper limit, the route planning system resolves the issue by changing the inspection time of the waypoint. Specifically, the route planning system first checks whether the number of adjustments already made has reached the preset upper limit (e.g., 5 times). If the upper limit is reached and the waypoint still does not meet the quality conditions, the route planning system will switch to adjusting the time dimension. The route planning system establishes a time adjustment window centered on the original timestamp of the current baseline waypoint, extending forward and backward by a preset time span (e.g., ±5 minutes). The size of this window needs to consider the overall task duration constraints and the time interval between adjacent waypoints to ensure that the adjustment does not cause task timing conflicts. The route planning system will then search for a more suitable inspection time within this time window.

[0090] Step S223: Within the time adjustment window, search forward or backward with a preset time step to generate one or more candidate timestamps; Here, the time step represents the time interval between two adjacent candidate time points; the candidate timestamp refers to the set of possible inspection times generated within the adjustment window. After establishing the time adjustment window, the route planning system needs to find suitable alternative time points within this window. Specifically, the route planning system sets an appropriate time step (e.g., 1 minute), which must be small enough to ensure search accuracy while also considering computational efficiency. Starting from the beginning of the time window, the route planning system generates candidate time points sequentially according to the set step size. To improve search efficiency, the route planning system employs a bidirectional search strategy, searching forward and backward simultaneously, prioritizing times closer to the original time.

[0091] For each generated candidate timestamp, the route planning system checks whether it conflicts with the times of other waypoints to ensure the rationality of the timing.

[0092] Step S224: Calculate the vector angle between the glare reflection vector and the photovoltaic panel normal vector corresponding to each candidate timestamp, and determine the candidate timestamp with the largest vector angle as the adjusted timestamp; Here, the vector angle refers to the angle between two vectors. After generating candidate timestamps, the flight path planning system needs to evaluate the observation conditions at each time point. Specifically, the system first calculates the corresponding solar position and photovoltaic panel attitude based on each candidate timestamp, then calculates the glare reflection vector at each moment, and calculates the angle between this vector and the photovoltaic panel normal vector. It should be noted that a larger angle means a greater deviation of the reflected light from the observation direction, resulting in less glare interference. The flight path planning system compares the angle values ​​of all candidate times and selects the time point with the largest angle as the new inspection time.

[0093] Step S225: Based on the adjusted timestamp, determine the new waypoint offset and recalculate the line-of-sight vector, the inspection tilt angle, and the glare avoidance angle. The first waypoint offset that meets the waypoint quality conditions is determined as the final waypoint offset. Step S226: Fit each offset waypoint to obtain the final inspection route.

[0094] By adopting the above technical solution, the flight path planning system first uniformly divides the photovoltaic array layout and plans the initial flight path based on the shortest path algorithm, ensuring the integrity of the inspection coverage and the optimality of the path. A dual waypoint quality assessment mechanism is introduced, which quantitatively evaluates the offset waypoints by calculating the inspection tilt angle and glare avoidance angle. When a waypoint does not meet the quality conditions, the flight path planning system makes precise distance adjustments based on the avoidance angle difference, and quickly converges to a position that meets the conditions through iterative optimization. Simultaneously, when spatial adjustments reach their upper limit and still cannot meet the conditions, the flight path planning system switches to temporal optimization, searching for the moment with the maximum vector angle within a time window to find the observation opportunity with minimal glare interference. This strategy of coordinated optimization in both spatial and temporal dimensions not only ensures that each waypoint simultaneously meets the requirements of observation quality and glare avoidance, but also effectively avoids oversaturation exposure of UAV-acquired images caused by specular reflection from the photovoltaic panels under complex lighting conditions, effectively improving the adaptability and reliability of the flight path planning.

[0095] Example 3 Based on the above embodiments, the route planning system in the embodiments of this invention will be described below from the perspective of hardware processing, referring to... Figure 5 The diagram shown is a schematic diagram of the physical device structure of a route planning system provided in an embodiment of this application.

[0096] It should be noted that, Figure 5 The structure of the route planning system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0097] like Figure 5 As shown, the route planning system includes a CPU 401, which can perform various appropriate actions and processes based on a program stored in the read-only memory ROM 402 or a program loaded from the storage section 408 into the random access memory RAM 403, such as performing the methods described in the above embodiments. The RAM 403 also stores various programs and data required for system operation. The CPU 401, ROM 402, and RAM 403 are interconnected via a bus 404. An I / O interface 405 is also connected to the bus 404.

[0098] The following components are connected to I / O interface 405: input section 406 including audio input devices, push-button switches, etc.; output section 407 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 408 including a hard disk, etc.; and communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 409 performs communication processing via a network such as the Internet. Drive 410 is also connected to I / O interface 405 as needed. Removable media 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 410 as needed so that computer programs read from them can be installed into storage section 408 as needed.

[0099] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the method in any of the embodiments of this application. Specifically, a system or apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the above embodiments is stored, and the computer (or CPU (Central Processing Unit) or MPU (Microprocessor Unit) of the system or apparatus may read and execute the program code stored in the storage medium.

[0100] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), it performs the functions defined in the system of this application.

[0101] It should be noted that the computer-readable storage medium shown in this invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. For example, a computer-readable storage medium can be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fiber, portable compact disc read-only memory (CD ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable storage medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable storage medium can be transmitted using any suitable medium, including but not limited to: wireless, wireline, optical fiber, RF, etc., or any suitable combination thereof.

[0102] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0103] The units described in the embodiments of the present invention can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0104] It should be noted that although several modules or units of the device for performing actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0105] In the several embodiments provided in this application, it should be understood that the disclosed systems, modules, and methods can be implemented in other ways. For example, the module embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between modules or units, and may be electrical, mechanical, or other forms.

[0106] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. This application is not limited to the exact structures described above and illustrated in the accompanying drawings, and it should not be considered that the specific implementation of this application is limited to these descriptions. For those skilled in the art, various changes and modifications made without departing from the concept of this application should be considered to fall within the protection scope of this application.

Claims

1. A method for determining the unmanned aerial vehicle (UAV) inspection route for a photovoltaic power station, characterized in that, include: Obtain inspection task information and construct an initial inspection route for the target inspection area based on the inspection task information; Determine the solar incidence vector of each reference waypoint timestamp of the initial inspection route and the photovoltaic panel normal vector of the photovoltaic panel in the target inspection area at each reference waypoint timestamp; Glare reflection vectors for each reference waypoint timestamp are generated based on the solar incident vector and the photovoltaic panel normal vector. Then, for each reference waypoint, the cross product of the glare reflection vector and the photovoltaic panel normal vector is calculated to obtain the safety offset vector for each reference waypoint. The safety offset vector is perpendicular to the glare reflection vector and perpendicular to the photovoltaic panel normal vector. Based on the safety offset vector of each reference waypoint, a preset safety offset distance is applied to each reference waypoint to obtain multiple first offset waypoints, and then each first offset waypoint is fitted to obtain the final inspection route.

2. The method for determining the unmanned aerial vehicle (UAV) inspection route for photovoltaic power plants according to claim 1, characterized in that, The inspection task information includes the inspection start time; the construction of the initial inspection route for the target inspection area based on the inspection task information includes: Obtain the photovoltaic array layout information of the target inspection area; Based on the photovoltaic array layout information, the target inspection area is divided into multiple target photovoltaic array areas, and the geometric center point of each target photovoltaic array area is determined as the reference waypoint. The multiple reference waypoints are sorted to generate an ordered path with the shortest total flight distance, and the flight time between each two adjacent reference waypoints on the ordered path is calculated based on the preset UAV flight speed. Starting from the inspection start time, the flight time on the ordered path is accumulated, and a unique timestamp is assigned to each of the reference waypoints to obtain the initial inspection route.

3. The method for determining the unmanned aerial vehicle (UAV) inspection route for photovoltaic power plants according to claim 2, characterized in that, The inspection task information also includes the location coordinates of the target inspection area; the determination of the solar incidence vector of each reference waypoint timestamp of the initial inspection route and the photovoltaic panel normal vector of the photovoltaic panel in the target inspection area at each reference waypoint timestamp includes: The inspection duration is determined based on the initial inspection route, and then the solar trajectory information during the operation of the initial inspection route is calculated by combining the position coordinates in the inspection task information; the solar trajectory information includes data on the changes of solar altitude angle and solar azimuth angle over time within the inspection duration; Based on the initial inspection route and the solar trajectory information, the solar incidence of each reference waypoint corresponding to the timestamp is calculated to obtain the solar incidence vector of each reference waypoint timestamp. The control parameters of the photovoltaic support within the target inspection area are obtained, and then the photovoltaic panel normal vector corresponding to the timestamp of each reference waypoint is determined based on the solar trajectory information. The control parameters include the spatial attitude of the support rotation axis, the rotation angle range, and the rotation control strategy.

4. The method for determining the unmanned aerial vehicle (UAV) inspection route for photovoltaic power plants according to claim 3, characterized in that, The step of acquiring the control parameters of the photovoltaic support within the target inspection area, and then determining the photovoltaic panel normal vector for each reference waypoint based on the solar trajectory information, includes: Based on the solar trajectory information, determine the solar altitude angle and solar azimuth angle of the timestamp corresponding to each of the reference waypoints; Based on the solar altitude angle, the solar azimuth angle, and the rotation control strategy, calculate the target rotation angle of the photovoltaic support at each of the timestamps; Based on the spatial attitude of the support rotation axis and the target rotation angle, a spatial coordinate transformation matrix for the photovoltaic panel attitude is established. Obtain the initial normal vector of the photovoltaic panel at the start time of the inspection, and substitute the initial normal vector into the spatial coordinate transformation matrix to obtain the photovoltaic panel normal vector corresponding to each timestamp.

5. The method for determining the unmanned aerial vehicle (UAV) inspection route for photovoltaic power plants according to claim 1, characterized in that, After applying a preset safety offset distance to each reference waypoint based on the safety offset vector of each reference waypoint to obtain multiple first offset waypoints, the method further includes: Determine the line-of-sight vector of the UAV camera at each of the first offset waypoints, wherein the line-of-sight vector is the geometric center of the target photovoltaic array region pointed from the first offset waypoint; Based on the line-of-sight vector, the inspection tilt angle and glare avoidance angle of each of the first offset waypoints are calculated. The inspection tilt angle is the angle between the line-of-sight vector and the corresponding photovoltaic panel normal vector, and the glare avoidance angle is the angle between the line-of-sight vector and the corresponding glare reflection vector. Determine whether the inspection tilt angle and the glare avoidance angle of each first offset waypoint meet preset waypoint quality conditions; the waypoint quality conditions include: the inspection tilt angle is less than a preset tilt angle upper limit threshold, and the glare avoidance angle is greater than a preset avoidance threshold. If the inspection tilt angle or the glare avoidance angle does not meet the preset waypoint quality conditions, the target offset waypoint that does not meet the waypoint quality conditions is adjusted until the adjusted target offset waypoint meets the waypoint quality conditions, and a second offset waypoint is determined.

6. The method for determining the unmanned aerial vehicle (UAV) inspection route for photovoltaic power plants according to claim 5, characterized in that, When the inspection tilt angle or the glare avoidance angle does not meet the preset waypoint quality conditions, the target offset waypoint that does not meet the waypoint quality conditions is adjusted until the adjusted target offset waypoint meets the waypoint quality conditions, and a second offset waypoint is determined, including: Calculate the difference between the glare avoidance angle corresponding to the target waypoint and the avoidance threshold; Based on the avoidance angle difference, determine the safety offset adjustment amount, and add the safety offset adjustment amount to the current safety offset distance to obtain a new safety offset distance; Based on the new safe offset distance and the safe offset vector corresponding to the reference waypoint, the adjusted target offset waypoint is determined, and the line-of-sight vector, the inspection tilt angle, and the glare avoidance angle are recalculated based on the adjusted target offset waypoint. When the adjusted target offset waypoint meets the waypoint quality condition, the adjusted target offset waypoint is determined as the second offset waypoint.

7. The method for determining the unmanned aerial vehicle (UAV) inspection route of a photovoltaic power station according to any one of claims 5-6, characterized in that, The method of adjusting the target offset waypoint that does not meet the preset waypoint quality conditions when the inspection tilt angle or the glare avoidance angle does not meet the preset waypoint quality conditions, until the adjusted target offset waypoint meets the waypoint quality conditions, and determining the second offset waypoint, further includes: If the number of adjustments to a target offset waypoint that does not meet the waypoint quality conditions reaches a preset limit and the waypoint quality conditions are still not met, the target reference waypoint corresponding to the target offset waypoint is determined, and the timestamp of the target reference waypoint is adjusted. Based on the adjusted timestamp, a new third offset waypoint is determined, and the line-of-sight vector, inspection tilt angle, and glare avoidance angle based on the third offset waypoint are recalculated. The first third offset waypoint that meets the waypoint quality conditions is determined as the final second offset waypoint. The step of determining the target reference waypoint corresponding to the target offset waypoint and adjusting the timestamp of the target reference waypoint includes: A time adjustment window is established centered on the timestamp corresponding to the target reference waypoint in the initial inspection route; Within the time adjustment window, a search is performed forward or backward at a preset time step to generate one or more candidate timestamps; Calculate the vector angle between the glare reflection vector and the photovoltaic panel normal vector corresponding to each candidate timestamp, and determine the candidate timestamp with the largest vector angle as the adjusted timestamp.

8. A device for determining the unmanned aerial vehicle (UAV) inspection route for a photovoltaic power station, characterized in that, include: The acquisition module is used to acquire inspection task information and construct an initial inspection route for the target inspection area based on the inspection task information. The first determining module is used to determine the solar incidence vector of each reference waypoint timestamp of the initial inspection route and the photovoltaic panel normal vector of the photovoltaic panel in the target inspection area at each reference waypoint timestamp. The second determining module is used to generate a glare reflection vector for each of the reference waypoint timestamps based on the solar incident vector and the photovoltaic panel normal vector, and then calculate the vector cross product of the glare reflection vector and the photovoltaic panel normal vector for each reference waypoint to obtain a safety offset vector for each reference waypoint; wherein, the safety offset vector is perpendicular to the glare reflection vector and the safety offset vector is perpendicular to the photovoltaic panel normal vector. The offset fitting module is used to apply a preset safe offset distance to each reference waypoint based on the safe offset vector of each reference waypoint to obtain multiple first offset waypoints, and then fit each of the first offset waypoints to obtain the final inspection route.

9. An electronic device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the method for determining the unmanned aerial vehicle (UAV) inspection route for photovoltaic power plants as described in any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the route planning system, the route planning system performs the method for determining the inspection route of a photovoltaic power station by a drone as described in any one of claims 1 to 7.

Images