A Measuring Device for Residual Thickness of Brake Shoe of Railcar Based on Deep Learning

Abstract

At present, the residual thickness of brake shoe of metro vehicles is mainly measured manually by naked eyes or simple ruler, which has some problems such as low detection efficiency, large subjective randomness and poor engineering applicability. Therefore, this paper proposes a device for measuring the residual thickness of brake shoes of railcar based on deep learning method. Firstly, a residual thickness measuring device includes parts of image acquisition module, image positioning and segmentation module, and image correction module. Then for each module, the article conducted the related experiments for verifying the accuracy of the system. The results show that the brake shoe residual thickness measurement device proposed in this paper has higher accuracy and better robustness than manual detection, and has obvious advantages in detection time consumption.