Aiming at the problem that the target area and background area are mixed,and the evolution law of substation main equipment defects is unknown,an infrared imaging analysis method based on power big data is proposed.After collec-ting the infrared image of the main substation equipment with infrared imaging technology,Otsu algorithm is used to seg-ment the target area and background area in the infrared image of the main substation equipment.Taking the segmented in-frared image of the main substation equipment and power big data as inputs,the defect detection results of the main substa-tion equipment are output through the hybrid deep learning neural network model.Input the defect detection results of the main substation equipment into RFPA2D software,analyze the primitive fracture of the defect detection results of the main substation equipment,and obtain the analysis results of the defect evolution law of the main substation equipment.The ex-perimental results show that the image of the main substation equipment collected by this method is highly consistent with the actual image.When segmenting the target area and background area of the infrared image of the main substation equip-ment,it is less affected by the contrast.It can effectively detect the defect type of the main equipment of the substation and analyze its defect evolution law.
power big datamain substation equipmentdefect evolution lawinfrared imagingwavelet transform
万方数据
维普
