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Bridge structures, after a period of exploitation, will be degraded for many reasons. It is necessary to assess the load rating to evaluate whether the bridge can continue to operate with the current load. Among the structural parameters, the vibration frequency is a parameter sensitive to changes in the actual condition of the structure. This article introduces a method combining vibration measurement results and an artificial neural network to evaluate bridge load ratings with the actual condition of the structure. The results of the proposed method are compared with those of the other load rating methods.

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Using Artificial Neural Network with Vibration Measurement Result for Prestressed Reinforced Concrete I Girder Bridge Load Rating Estimation

  • 会议论文

  • 发表日期：

    2026年

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  • Nguyen Huu Hung,
  • Dam Minh Hung

摘要

Bridge structures, after a period of exploitation, will be degraded for many reasons. It is necessary to assess the load rating to evaluate whether the bridge can continue to operate with the current load. Among the structural parameters, the vibration frequency is a parameter sensitive to changes in the actual condition of the structure. This article introduces a method combining vibration measurement results and an artificial neural network to evaluate bridge load ratings with the actual condition of the structure. The results of the proposed method are compared with those of the other load rating methods.