Multi-scale Perspective Bridge Damage Detection and ServicePerformance Evaluation Research: A Review
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Affiliation:

1.School of Civil Engineering;2.National Key Laboratory of Bridge Intelligent and Green Construction,Southwest Jiaotong University;3.School of Civil Engineering, Southwest Jiaotong University;4.Sichuan Jiaoda Engineering Testing Consulting Co,Ltd;5.College of Economic and Management,North University of China

Clc Number:

U446.3

Fund Project:

National Natural Science Foundation of China (No. 52322811), Sichuan Science and Technology Program (No. 2020YJ0081), Scientific Program of Sichuan Jiaoda Engineering Testing Consulting Co., Ltd (KYL202305-0143)

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    Abstract:

    Bridge inspection and service performance evaluation are critical technologies for ensuring the safe operation of bridges. This paper systematically reviews the academic progress, existing achievements, and future trends in the field of bridge damage detection and assessment, focusing on the multi-scale perspective. The research is explored from three different scales: macro, meso, and sub-micro. At the macro scale, the evolution of bridge feature detection methods is deeply analyzed, revealing the trend of transforming into rapid detection technologies based on vehicle response. At the meso and sub-micro scales, due to the complexity of bridge surface damage, existing research focuses on recognition methods based on computer vision. In terms of service performance evaluation, the existing methods for short-term bridge condition assessment and long-term condition prediction are summarized. The comprehensive analysis shows that the current bridge inspection technology has been effective in identifying bridge damage features. However, future research should still focus on two directions: macro damage identification based on vehicle response and meso and sub-micro damage identification based on computer vision. Both directions have shown great application potential. Future research should further optimize the vehicle-bridge coupling response model and improve its applicability to different forms of macro-scale damage. Studying the mapping relationship between meso and sub-micro-scale damage images and bridge mechanical characteristics. Improving the accuracy of detection with researching on the correlation of multi-scale damage. Especially, more practical bridge service performance evaluation methods are explored with engineering practice.

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History
  • Received:July 12,2024
  • Revised:August 08,2024
  • Adopted:September 11,2024
  • Online:
  • Published:
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