Method for detecting residual thickness of electric collector shoe of metro linear motor vehicle based on deep learning

Jin Huo Ma; Qing Bo Wu; Jing Wang

doi:10.1117/12.2631641

18 March 2022 Method for detecting residual thickness of electric collector shoe of metro linear motor vehicle based on deep learning

Jin Huo Ma, Qing Bo Wu, Jing Wang

Author Affiliations +

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 1216821 (2022) https://doi.org/10.1117/12.2631641
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

At present, the wear of the electric collector shoe sliders of subway vehicles is mainly detected by naked eyes or simple rulers. There are problems such as low efficiency and low acquisition, and it is different to meet the needs of engineering applications. In this regard, this paper proposes a method for detecting the thickness of the electric collector shoe slider by the deep learning. First, establish the collector shoe slider dataset for the segmentation neural network method; second, use the attention mechanism and sub-pixel variable layer to optimize and train the original DeepLabV3 + neural network; finally, the optimized neural network and the traditional neural network method are used for comparative experts. The results show that the method proposed in this paper can significantly import the acquisition of the wear detection of the collector shoe slider.

Citation Download Citation

Jin Huo Ma, Qing Bo Wu, and Jing Wang "Method for detecting residual thickness of electric collector shoe of metro linear motor vehicle based on deep learning", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 1216821 (18 March 2022); https://doi.org/10.1117/12.2631641

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