On-line detection method of insulator zero-value fault based on image features and YOLOv3 algorithm

Insulators, as one of the important components of transmission lines, mainly play the role of isolating and supporting conductors. Because of the harsh environment in which insulators are located, it is easy to cause the problem of missing, which leads to the zero-value fault of transmission lines. Therefore, an online detection method of insulator zero-value fault based on image characteristics and YOLOv3 algorithm is proposed. Traverse the gray level and calculate the maximum slope. Through piecewise linear change, the preprocessing result of insulator zero-value fault online detection data is obtained, and the average value of regional pixels is calculated. Combined with image characteristics and YOLOv3 algorithm, online fault detection is realized. The experimental results show that this method can detect all missing faults, and the obtained missing values are basically consistent with the actual set values, with an accuracy rate of 99% and strong detection ability.