Intelligent fault detection of high voltage line based on the Faster R-CNN

Abstract To realize intelligent fault detection of high voltage line, a deep convolution neural network method based on Faster R-CNN method is proposed to locate the broken insulators and bird nests. With the region proposal network, the Faster R-CNN chooses a random region in the features of the image as the proposal region, and trains them to get the corresponding category and location for a certain component in the image. Since the internal and regional features of the image can be learned, the Faster R-CNN method transforms the problem of target classification into the problem of target detection and recognition. Based on the ResNet-101 network model, the damage of insulators and bird nests in the electric power line can be located effectively.

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