CN-121994233-A - Unmanned aerial vehicle routing inspection path planning method based on large-scale photovoltaic power station partition cooperation

CN121994233ACN 121994233 ACN121994233 ACN 121994233ACN-121994233-A

Abstract

The invention discloses a method for planning a regional collaborative unmanned aerial vehicle routing inspection path of a photovoltaic power station in a large mountain and hilly terrain, which comprises the following steps of S1, constructing a high-precision three-dimensional geographic model of the photovoltaic power station and extracting terrain features, S2, dividing the power station into a plurality of routing inspection subareas based on the terrain features and the photovoltaic array electrical topology, S3, establishing a path cost model taking spiral flight surrounding the hilly structure as a core for each subarea, enabling the flight track of the unmanned aerial vehicle to be matched with the mountain terrain height through the spiral flight path mode surrounding the hilly, avoiding frequent sharp lifting of a traditional zigzag or broken line path, greatly reducing flight energy consumption and risk, improving flight stability, enabling a spiral path to provide a more consistent and more vertical observation angle for the photovoltaic panel, facilitating improvement of defect identification accuracy, enabling a continuous smooth path to reduce unnecessary acceleration and deceleration and hovering, and improving coverage efficiency.

Inventors

ZHAO GUOLI
Du Panyi
Di Mingming
YUAN YAOKAI
HU FU

Assignees

云鹰智维能源科技有限公司
英利集团有限公司

Dates

Publication Date: 20260508
Application Date: 20260119

Claims (8)

1. A method for planning a patrol path of an unmanned aerial vehicle with a large-scale mountain and hilly terrain photovoltaic power station in a partition cooperation mode is characterized by comprising the following steps of S1, constructing a high-precision three-dimensional geographic model of the photovoltaic power station, extracting terrain features, S2, dividing the power station into a plurality of patrol subareas based on the terrain features and the photovoltaic array electrical topology, S3, establishing a path cost model taking spiral flight surrounding a hilly structure as a core for each subarea, S4, distributing subareas to each unmanned aerial vehicle and planning a global transfer channel according to the number and the cruising ability of the unmanned aerial vehicle, S5, generating a specific three-dimensional spiral patrol path for each unmanned aerial vehicle in each allocated subarea, S6, conducting smoothing and speed planning according with unmanned aerial vehicle dynamics on the spiral path, S7, conducting space-time conflict detection and resolution on a plurality of unmanned aerial vehicle paths, S8, packaging and issuing a final path and reserving a dynamic reprofiling interface.
2. The method for planning the inspection path of the unmanned aerial vehicle with the cooperation of the regional partitions of the photovoltaic power stations of the large mountain and hilly terrain is characterized by comprising the steps of taking the high points of the hilly terrain in the subareas as axes, generating a three-dimensional spiral descending or ascending base line adapting to the fluctuation of the terrain, generating a spiral path family covering all photovoltaic arrays of the subarea through parallel offset based on the base line, and comprehensively evaluating the continuous smoothness of flight along the spiral path, the coverage quality of the photovoltaic panel, the obstacle avoidance difficulty and the communication link quality.
3. The unmanned aerial vehicle inspection path planning method based on the regional cooperation of the large-scale mountain and hilly terrain photovoltaic power stations according to claim 1 or 2, wherein the regional is characterized by specifically adopting an adaptive clustering algorithm which integrates the terrain relief, the slope consistency, the integrity of the photovoltaic array electrical units and the historical fault area information.
4. The unmanned aerial vehicle inspection path planning method based on the large mountain and hilly terrain photovoltaic power station partition cooperation is characterized in that task allocation in S4 specifically builds a multi-objective optimization model aiming at minimizing the maximum sub-area completion time and balancing the total flight distance of each unmanned aerial vehicle, and solves the problem by adopting a genetic algorithm or a particle swarm algorithm.
5. The unmanned aerial vehicle inspection path planning method based on the regional cooperation of the large-scale mountain and hilly terrain photovoltaic power stations according to claim 1 is characterized in that the three-dimensional spiral inspection path is generated in S5, and specifically, an algorithm combining a gradient descent method and cubic spline curve optimization is adopted to ensure continuity, smoothness and flyability of the path in a three-dimensional space.
6. The unmanned aerial vehicle routing inspection path planning method based on the large mountain and hilly terrain photovoltaic power station partition cooperation is characterized in that the path smoothing and speed planning in S6 specifically comprises the steps of smoothing a turning transition section of a spiral path by adopting a Dubins curve or Clothoid curve, and planning self-adaptive cruising speed according to the curvature of the path, the shooting point position and the terrain fluctuation.
7. The method for planning the inspection path of the unmanned aerial vehicle with the cooperation of the large mountain and hilly terrain photovoltaic power station partitions according to claim 1, wherein the conflict resolution in the step S7 specifically comprises mapping all unmanned aerial vehicle paths to a unified space-time coordinate system, detecting that the spatial position conflict overlaps with a time window, and eliminating the conflict by allocating different passing time or flight height layers to the conflicting unmanned aerial vehicles.
8. The method for planning the inspection path of the unmanned aerial vehicle with the cooperation of the subareas of the photovoltaic power stations in the hilly and hilly areas of the large-scale mountainous area according to claim 1, wherein the dynamic re-planning interface in the step S8 is used for responding to real-time perceived sudden obstacle, bad weather or unmanned aerial vehicle faults and carrying out local rapid re-planning on the paths of the current subarea and the subsequent subareas of the affected unmanned aerial vehicle.

Description

Unmanned aerial vehicle routing inspection path planning method based on large-scale photovoltaic power station partition cooperation Technical Field The invention belongs to the technical field of unmanned aerial vehicle inspection and path planning, and particularly relates to an unmanned aerial vehicle inspection path planning method with large-scale photovoltaic power station partition cooperation. Background As the photovoltaic power generation industry expands to complicated terrain areas such as mountain areas, hills and the like, the power station scale is increasingly large, and the patrol maintenance work of the photovoltaic power generation industry faces a great challenge. Unmanned aerial vehicle inspection technology has become an important means for solving this problem. However, in the large-scale mountain area hilly photovoltaic power station scene, the existing unmanned aerial vehicle inspection path planning method mostly adopts a two-dimensional plane planning idea, or simply adopts a traditional 'bow' -shaped, broken line round trip type or grid coverage type path in a three-dimensional space. The flight mode is extremely high in energy consumption, seriously shortens effective operation time, and puts severe requirements on flight control stability and fuselage structural strength, increases safety risks, and meanwhile, the rapid attitude change causes that a tripod head camera is difficult to keep stable focusing and vertical observation on a photovoltaic panel, so that accuracy of defect identification is affected. Therefore, the invention provides the unmanned aerial vehicle routing inspection path planning method with the large-scale photovoltaic power station partition cooperation, so that the flight track of the unmanned aerial vehicle and the geographic features of mountains and hills are highly adaptively fused, and the unmanned aerial vehicle routing inspection path planning method in a three-dimensional space is realized. Disclosure of Invention The unmanned aerial vehicle routing inspection path planning method comprises the following steps of S1, constructing a high-precision three-dimensional geographic model of a photovoltaic power station and extracting geographic features, S2, dividing the power station into a plurality of routing inspection subareas based on the geographic features and the electrical topology of a photovoltaic array, S3, establishing a path cost model taking spiral flight surrounding a hilly structure as a core for each subarea, S4, distributing subareas to each unmanned aerial vehicle according to the number and the cruising ability of the unmanned aerial vehicle and planning a global transfer channel, S5, generating a specific three-dimensional spiral routing inspection path for each unmanned aerial vehicle in each subarea distributed by the unmanned aerial vehicle, S6, conducting smoothing and speed planning conforming to unmanned aerial vehicle dynamics on the spiral path, S7, conducting space-time conflict detection and digestion on a multi-machine path, S8, issuing a final path and reserving a dynamic rescheduling interface. The method for establishing the spiral flight path cost model surrounding the hilly structure in the S3 specifically comprises the steps of taking a hilly terrain high point in a subarea as an axis, generating a three-dimensional spiral descending or ascending base line adapting to terrain fluctuation, generating a spiral path family covering all photovoltaic arrays of a subarea through parallel offset based on the base line, and comprehensively evaluating the continuity smoothness of flight along the spiral path, the coverage quality of a photovoltaic panel, the obstacle avoidance difficulty and the communication link quality. As a preferable technical scheme of the invention, the subareas in S2 specifically adopt an adaptive clustering algorithm which fuses the topography relief, the slope consistency, the integrity of the photovoltaic array electrical unit and the historical fault area information. As a preferable technical scheme of the invention, task allocation in S4 is realized by specifically constructing a multi-objective optimization model which aims at minimizing the maximum sub-zone completion time and balancing the total flight distance of each unmanned aerial vehicle, and solving by adopting a genetic algorithm or a particle swarm algorithm. As a preferable technical scheme of the invention, the generation of the three-dimensional spiral inspection path in S5 specifically adopts an algorithm combining a gradient descent method and cubic spline curve optimization so as to ensure continuity, smoothness and flyability of the path in a three-dimensional space. As a preferable technical scheme of the invention, the path smoothing and speed planning in S6 specifically comprises the steps of smoothing the turning transition section of the spiral path by adopting a Dubins curve or Clothoid curve, and planning the self-ad