The use of ground-penetrating radar (GPR) technology in railway maintenance and inspection has gained significant attention in recent years due to its non-destructive and efficient nature. This paper explores the application and development of artificial intelligence (AI) in conjunction with GPR for the assessment of ballasted tracks. The integration of AI algorithms enhances the interpretation of GPR data, providing a more accurate and automated method for detecting and predicting potential trackbed fouling. This article explores the innovative applications of machine learning and deep learning in GPR data processing for railway track engineering prospection, evaluating their potential, limitations, and future prospects, aiming to contribute to the advancement of railway infrastructure monitoring, with a focus on improving reliability, safety, and maintenance efficiency.


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    Titel :

    AI-Based Ballasted Track GPR Application and Development


    Beteiligte:
    Indraratna, Buddhima (Herausgeber:in) / Rujikiatkamjorn, Cholachat (Herausgeber:in) / Qin, Xuanyang (Autor:in) / Peng, Zhan (Autor:in) / Jing, Guoqing (Autor:in)


    Erscheinungsdatum :

    27.10.2024


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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