Pantograph-catenary arcing refers to an abnormal phenomenon occurring in pantograph-catenary system due to poor contact or other factors, which significantly impacts the normal operation of high-speed railway. Therefore, the detection of arcing occurrences holds significant importance for the intelligent maintenance of pantograph-catenary systems. However, the scarcity of arcing data in pantograph-catenary datasets limits the efficacy of supervised learning methods for arcing detection. To address this issue, we propose a novel pantograph-catenary arcing detection model that integrates semantic segmentation with generative adversarial networks. The model first modifies the loss function of the U $^2$   2 -Net network to tailor it specifically for pantograph-catenary semantic segmentation. To generate finer normal pantograph-catenary images, attention mechanism is incorporated into the SPADE-based pantograph-catenary scene generation model. Finally, an improved differencing method is employed to compute the arcing image by subtracting the generated normal pantograph-catenary image from the actual pantograph-catenary image. The experimental results validate the effectiveness of the method for pantograph-catenary arcing detection in the absence of prior arcing knowledge, with a recall rate of 75.3% and an F1-Score of 69.63%. Compared to other advanced pantograph-catenary arcing methods, this method exhibits superior performance.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A pantograph-catenary arcing detection model for high-speed railway based on semantic segmentation and generative adversarial network


    Additional title:

    X. LIU ET AL.
    INTERNATIONAL JOURNAL OF RAIL TRANSPORTATION


    Contributors:
    Liu, Xiaohong (author) / Wang, Xiaoyu (author) / Quan, Wei (author) / Gu, Guoxin (author) / Xu, Xiaoqian (author) / Gao, Shibin (author)

    Published in:

    Publication date :

    2025-07-04


    Size :

    22 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Modeling pantograph-catenary arcing

    Zhu, G.-y | Online Contents | 2016


    Modeling pantograph–catenary arcing

    Zhu, Guang-ya / Gao, Guo-qiang / Wu, Guang-ning et al. | SAGE Publications | 2016


    Contact-Mechanics-Based Catenary–Pantograph Interaction Model for High-Speed Electric Railway Systems

    Roy, Suprateek / Sarkar, Srikrishna / Lokireddy, Susritha et al. | IEEE | 2025


    Bionic Vision-Based Pantograph–Catenary Contact Point Detection Study in China High-Speed Railway

    Wu, Zaixin / Huang, Shize / Yu, Liangliang et al. | Springer Verlag | 2020


    Bionic Vision-Based Pantograph—Catenary Contact Point Detection Study in China High-Speed Railway

    Wu, Zaixin / Huang, Shize / Yu, Liangliang et al. | British Library Conference Proceedings | 2020