With the widespread use of plate rubber bearings in bridge construction, there is an urgent need for an objective, efficient, and labor-saving disease detection method to improve the quality and efficiency of bridge maintenance. In this study, three common bridge plate-rubber-bearing diseases are the research objects, along with normal bearings. A bridge plate-rubber-bearing disease classification model based on the VGG16 network was constructed using transfer learning methods. The study compared the performance of four deep convolutional neural network models obtained by training from scratch and transfer learning. To further enhance model performance, data augmentation was applied during transfer learning on the VGG16 model constructed in this study. The results showed that the data set enhanced with image augmentation presented an improvement in overall recognition accuracy of 18% in the fine-tuning transfer learning algorithm of the VGG16 model compared with training from scratch. This validates the effectiveness and feasibility of the proposed model and provides strong support that it improves the efficiency of identifying and classifying diseases in bridge rubber bearings and facilitates post-bridge maintenance.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Visual-Based Deep Convolutional Neural Network Method for Detecting Damage in Bridge Plate Rubber Bearings


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Chen, Yongkang (author) / Li, Weirong (author) / Sun, Guangjun (author) / Chen, Bo (author)


    Publication date :

    2025-03-03




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    A Damage Localization Approach for Rahmen Bridge Based on Convolutional Neural Network

    Lee, Kanghyeok / Byun, Namju / Shin, Do Hyoung | Springer Verlag | 2020


    Characterization of rubber vulcanizates for bridge bearings

    Eyre, R. / Stevenson, A. | TIBKAT | 1991


    Structural Damage Detection using Deep Convolutional Neural Network and Transfer Learning

    Feng, Chuncheng / Zhang, Hua / Wang, Shuang et al. | Springer Verlag | 2019


    Structural Damage Detection using Deep Convolutional Neural Network and Transfer Learning

    Feng, Chuncheng / Zhang, Hua / Wang, Shuang et al. | Online Contents | 2019