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Intelligent Fault Diagnosis for Bridge via Modal Analysis

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  • Wenjun Zhuang

    (Yunnan Communications Vocational and Technical College, China)

Abstract

Due to natural disasters and man-made reasons, bridges are prone to structural damage during long-term usage, which reduces the associated carrying capacity, increases natural aging, and reduces safety. It is urgent to monitor the health status of bridge structure via intelligent technology. This paper proposes a bridge fault recognition structure. First, the signals of bridge parameter are collected by using distributed sensors. Then, the collected signals are processed by signal processing to extract the features in time and frequency domain. Lastly, the extracted features are used to learn an intelligent classifier. The large margin distribution machine is adopted as a classification model. The experimental results have proven the feasibility of the proposed bridge fault recognition structure.

Suggested Citation

  • Wenjun Zhuang, 2022. "Intelligent Fault Diagnosis for Bridge via Modal Analysis," International Journal of Information System Modeling and Design (IJISMD), IGI Global, vol. 13(2), pages 1-12, April.
    • Handle: RePEc:igg:jismd0:v:13:y:2022:i:2:p:1-12
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    References listed on IDEAS

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    1. Chunfeng Wan & Zhenwei Zhou & Siyuan Li & Youliang Ding & Zhao Xu & Zegang Yang & Yefei Xia & Fangzhou Yin, 2019. "Development of a Bridge Management System Based on the Building Information Modeling Technology," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
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