Photovoltaic panel fault detection and recognition method and device and unmanned aerial vehicle

Abstract

The invention discloses a photovoltaic panel fault detection and identification method. The method comprises the following steps of preprocessing a photovoltaic panel infrared video, and extracting frame by frame to obtain the photovoltaic panel image data after perspective transformation; determining a photovoltaic array area; extracting to obtain a photovoltaic panel array image; for the extracted photovoltaic panel array image, removing invalid lines line by line by adopting a threshold method, and extracting to obtain the small photovoltaic panel area images; calculating a pixel mean valueand a variance of each small photovoltaic panel area image, and carrying out fault detection and fault category judgment by adopting a threshold method; numbering the faults by calculating a fault photovoltaic panel characteristic function value, obtaining the fault position information through calculation in combination with the unmanned aerial vehicle route data and a photovoltaic panel numbersequence, wherein the fault position information comprises the number and the position of the photovoltaic panel where a fault is located. According to the invention, the photovoltaic panel fault detection can be carried out automatically, the fault images, fault types and fault positions are outputted, and the workers of a photovoltaic power station can determine the fault information timely andconveniently for photovoltaic panel maintenance.

Description

technical field [0001] The present invention relates to the technical field of digital image processing, in particular to a photovoltaic panel fault detection and identification method, device and unmanned aerial vehicle. Background technique [0002] Photovoltaic is the abbreviation of solar photovoltaic power generation system. Photovoltaic panel is a new type of power generation device that uses the photovoltaic effect of semiconductor materials to directly convert solar radiation energy into electrical energy. Due to the particularity of the photovoltaic power generation industry, photovoltaic power plants are often located in remote locations, with numerous equipment and a wide distribution area. The large construction scale and remote location determine the high complexity and difficulty of the operation and maintenance inspection work of photovoltaic plants. At present, the methods for photovoltaic panel fault detection include manual inspection method, laser detectio...

AI Technical Summary

Problems solved by technology

Due to the particularity of the photovoltaic power generation industry, photovoltaic power plants are often located in remote locations, with numerous equipment and a wide distribution area. The large construction scale and remote location determine the high complexity and difficulty of the operation and maintenance inspection work of photovoltaic plants

At present, the methods for photovoltaic panel fault detection include manual inspection method, laser detection method, automatic inspection method, etc. Among these methods, manual inspection method is inefficient. When applied to large-scale photovoltaic power plants in actual production and life, manual inspection method Patrol inspection is time-consuming and labor-intensive; laser detection method is a non-contact method. Although this method has high spatial resolution, it has not been well popularized due to the disadvantage of high cost.

[0003] Patent document CN110768628A discloses a photovoltaic array fault detection method, which uses a voltage sensor to collect data, relies on many electronic components, and has poor portability

Patent document CN109525194B discloses a method and system for detection and identification of faulty photovoltaic panels. The method realizes non-contact detection based on computer vision technology. It is impossible to number the fault and determine the fault location information, which is not conducive to the subsequent troubleshooting of workers

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