A Review of Vibration-Based Scour Diagnosis Methods for Bridge Foundation

Zhenhao Zhang, Guowei Lin, Xiaopeng Yang, Shilin Cui, Yan Li (), Xueqing Shi and Zhongyu Han
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Zhenhao Zhang: School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Guowei Lin: Jinan Urban Construction Group Co., Ltd., Jinan 250031, China
Xiaopeng Yang: School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Shilin Cui: School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Yan Li: School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Xueqing Shi: School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Zhongyu Han: School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China

Sustainability, 2023, vol. 15, issue 10, 1-25

Abstract: Foundation scour poses a serious threat to bridge safety in the whole life cycle and leads to many bridge failure incidents. Recently, as an important subfield of bridge structural health monitoring, vibration-based scour diagnosis methods have garnered widespread attention, particularly due to their rapid and low-cost features, which overcomes the difficulties of complex equipment installation associated with the traditional approaches. Recent advances of this method within the last decade are reviewed in this paper. Firstly, the principle of scour diagnosis and vibration excitation methods are introduced. Then, existing qualitative and quantitative studies on scour diagnosis are reviewed, respectively. The former refers to identifying the scour location based on the bridge dynamic characteristics or dynamic response changes, and the latter refers to identifying scour depth based on model updating or machine learning methods. Based on the above review, some important but neglected issues are summarized and discussed in depth, and some challenges and future trends are proposed, including innovative excitation methods, mitigation of environmental conditions interference, soil–structure interaction prediction and application of machine learning techniques.

Keywords: bridge scour diagnosis; dynamic behavior; model updating; machine learning; soil–structure interaction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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