关键词: 零值绝缘子, 红外热像, Logistic回归分析, 最小外接矩形, 纹理特征

Abstract: The zero resistance insulator is one of the important reasons causing grounded fault of transmission and distribution network. The key of detecting zero resistance insulators by infrared thermal imaging is to obtain the optimal and appropriate infrared thermal image features. An infrared thermal image feature selection method based on Logistic regression analysis is proposed. The infrared thermal image is denoised with median filtering and wavelet adaptive diffusion, and the contrast of the image is enhanced by means of gray stretching. The image is segmented to binary image with two-dimensional maximum entropy threshold. After binary image filling, the minimum enclosing rectangle around the disc surface of insulator string is intercepted automatically to obtain rectangle image of the insulator string area, through gray-gradient co-occurrence matrix, 13 texture features of rectangle area are extracted, and 14 characteristic parameters consisting of pollution class and texture features are screened by Logistic regression analysis, with 7 parameters among them having significant influence on the classification result. The experiments show that the proposed selection method is simple, and can effectively screen characteristic parameters and eliminate redundant data.

Key words: zero resistance insulator, infrared thermal image, Logistic regression analysis, minimum enclosing rectangle, texture feature