A Method of Insulator Fault Detection from Airborne Images

In this paper, a new method of insulator fault detection by texture feature sequence is proposed. Morphology, Hough transform line detection and statistic texture feature are applied to this method. Because there are some noises during image shooting, it is necessary that the insulator image should be preprocessed and corrected. The preprocessing includes image grayness, image enhancement and morphological processing. The insulator tilt correction is based on Hough transform line detection. Then, the processed insulator image is separated into ten parts. Each part of ten parts is featured by seven texture values. The matrix is constructed by ten columns which represent ten parts and seven rows which represent seven texture features. Each row of the matrix is defined as a sequence. According to the analysis of seven feature sequence curves, three feature sequence curves are selected because they are active. A fault feature formula that is named CMV is made of the three features. Insulator fault is detected by CMV curve. The position of fault is located by the biggest vale of CMV curve. Experimental results indicate the proper morphological processing improves the precision of Hough transform line detection and the insulator fault is detected and the position of fault is located by the proposed method accurately.