High Voltage Cable X-Ray Digital Image Depth Processing and Technology of Buffer Layer Defect Intelligent Recognition
Liu Sanwei, Zhang Jun, Xie Yi, Jianjia Duan, Fuyong Huang, Duan Xiaoli, Zeyu Zeng
Abstract
High voltage cable is an important basic equipment for city power supply. Existing research shows that: the method of digital X-ray imaging can realize the non-destructive detection of power cable, it belongs to the new detection technology in the field of cable defect detection, at present, there is no deep X-ray digital image processing and defect recognition method, and it can not directly detect the cable ontology and defect recognition from the original digital image. Therefore, this article on the depth of power cable X-ray digital image processing and intelligent recognition technology carried out research, buffer layer defects using gray processing technology, the original image grayscale range compression to the human eye can recognize, and defect identification, and the traditional convolution neural network and the convolution neural network (CNN) FCN image data for training, implementation of the intelligent identification of power cable buffer layer defects. The results show that compared with traditional convolutional neural network (CNN), the full convolutional neural network (FCN) proposed in this paper has a clearer and more intuitive recognition effect.