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A Critical Review for Trustworthy and Explainable Structural Health Monitoring and Risk Prognosis of Bridges with Human-In-The-Loop

Author

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  • Zhe Sun

    (Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
    The Key Laboratory of Urban Security and Disaster Engineering of the Ministry of Education, Beijing University of Technology, Beijing 100124, China)

  • Tiantian Chen

    (School of Mechanics and Civil Engineering, China University of Mining & Technology, Beijing 100083, China)

  • Xiaolin Meng

    (Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
    The Key Laboratory of Urban Security and Disaster Engineering of the Ministry of Education, Beijing University of Technology, Beijing 100124, China)

  • Yan Bao

    (Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
    The Key Laboratory of Urban Security and Disaster Engineering of the Ministry of Education, Beijing University of Technology, Beijing 100124, China)

  • Liangliang Hu

    (Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
    The Key Laboratory of Urban Security and Disaster Engineering of the Ministry of Education, Beijing University of Technology, Beijing 100124, China)

  • Ruirui Zhao

    (CUCDE Environmental Technology Co., Ltd., Beijing 100088, China)

Abstract

Trustworthy and explainable structural health monitoring (SHM) of bridges is crucial for ensuring the safe maintenance and operation of deficient structures. Unfortunately, existing SHM methods pose various challenges that interweave cognitive, technical, and decision-making processes. Recent development of emerging sensing devices and technologies enables intelligent acquisition and processing of massive spatiotemporal data. However, such processes always involve human-in-the-loop (HITL), which introduces redundancies and errors that lead to unreliable SHM and service safety diagnosis of bridges. Comprehending human-cyber (HC) reliability issues during SHM processes is necessary for ensuring the reliable SHM of bridges. This study aims at synthesizing studies related to HC reliability for supporting the trustworthy and explainable SHM of bridges. The authors use a bridge inspection case to lead a synthesis of studies that examined techniques relevant to the identified HC reliability issues. This synthesis revealed challenges that impede the industry from monitoring, predicting, and controlling HC reliability in bridges. In conclusion, a research road map was provided for addressing the identified challenges.

Suggested Citation

  • Zhe Sun & Tiantian Chen & Xiaolin Meng & Yan Bao & Liangliang Hu & Ruirui Zhao, 2023. "A Critical Review for Trustworthy and Explainable Structural Health Monitoring and Risk Prognosis of Bridges with Human-In-The-Loop," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6389-:d:1118687
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    References listed on IDEAS

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    Cited by:

    1. Abdullah Caliskan & Conor O’Brien & Krishna Panduru & Joseph Walsh & Daniel Riordan, 2023. "An Efficient Siamese Network and Transfer Learning-Based Predictive Maintenance System for More Sustainable Manufacturing," Sustainability, MDPI, vol. 15(12), pages 1-23, June.
    2. Jiaxin Yang & Yan Bao & Zhe Sun & Xiaolin Meng, 2024. "Computer Vision-Based Real-Time Identification of Vehicle Loads for Structural Health Monitoring of Bridges," Sustainability, MDPI, vol. 16(3), pages 1-20, January.

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