Railroad transportation is an essential component of national economic development, providing crucial support for safe and efficient transportation. The quality of rail infrastructure directly impacts the efficiency and safety of train operation. Therefore, the timely and accurate detection of rail surface defects is a critical element of railroad operation and safety management. This paper examines the technology of railroad track surface detection and proposes a novel defect detection method based on image processing. The proposed method utilizes a high-resolution digital camera to capture images of the rail surface and eliminates noise and lighting effects using pre-processing techniques. Next, a feature extraction algorithm is employed to extract the features of rail surface defects, and is used to classify and identify them. Experimental results demonstrate that the proposed method accurately detects various defects on the rail surface.


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    Title :

    Research on Surface Defect Detection Technology of Railway Tracks Based on Image Processing


    Additional title:

    Mechan. Machine Science


    Contributors:
    Ball, Andrew D. (editor) / Ouyang, Huajiang (editor) / Sinha, Jyoti K. (editor) / Wang, Zuolu (editor) / Liu, Guiyi (author) / Zhang, Chao (author) / Wang, Jianguo (author) / Chi, Yuliang (author) / Xu, Shuai (author)

    Conference:

    International conference on the Efficiency and Performance Engineering Network ; 2023 ; Huddersfield, United Kingdom August 29, 2023 - September 01, 2023
    International Conference on Maintenance Engineering ; 2023 ; Huddersfield, United Kingdom
    August 29, 2023 - September 01, 2023
    International Workshop on Defence Applications of Multi-Agent Systems ; 2023 ; Huddersfield, United Kingdom
    August 29, 2023 - September 01, 2023



    Publication date :

    2024-05-30


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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