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

  • Zhenhao Zhang
  • , Guowei Lin
  • , Xiaopeng Yang
  • , Shilin Cui
  • , Yan Li*
  • , Xueqing Shi
  • , Zhongyu Han
  • *Corresponding author for this work
  • School of Transportation Science and Engineering, Harbin Institute of Technology
  • Jinan Urban Construction Group Co. Ltd.

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish
Article number8210
JournalSustainability (Switzerland)
Volume15
Issue number10
DOIs
StatePublished - May 2023
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • bridge scour diagnosis
  • dynamic behavior
  • machine learning
  • model updating
  • soil–structure interaction

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