Abstract:In the conventional defect detection methods, panel defects are mainly detected based on the abnormal status data of the photovoltaic power plant panel. The detection results have certain randomness, resulting in unclear defect detection results. Therefore, the UAV image technology is used to design a defect detection method for photovoltaic power plant panel. The defect features in the image are extracted, combined with the UAV image technology, the defect image is separated from the complete image through the gray level co-occurrence matrix, the defect location of the visible light image is recognized, and the defect image is placed in the photovoltaic panel defect detection model for further detection, so that the image texture features and shape features are highly integrated, so as to achieve the accurate detection of photovoltaic power plant panel defects. By means of comparative experiments, it is verified that the detection method has higher detection confidence and detection accuracy, which can be applied in real life.