Damage Detection of Continuous Beam Bridge Based on Maximum Successful Approximation Approach of Wavelet Coefficients of Vehicle Response

In view of problems such as closed traffic, the large number of sensors required, and the labor-intensive and time-consuming nature of previous bridge detection, this paper analyzes the dynamic response of the vehicle body of the continuous girder bridge under the action of vehicle load. Based on th...

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Bibliographic Details
Main Authors: Liu, K. (Author), Qi, H. (Author), Sun, Z. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Online Access:View Fulltext in Publisher
Description
Summary:In view of problems such as closed traffic, the large number of sensors required, and the labor-intensive and time-consuming nature of previous bridge detection, this paper analyzes the dynamic response of the vehicle body of the continuous girder bridge under the action of vehicle load. Based on theoretical analysis and formula derivation, a new method of bridge damage detection based on coupled vehicle–bridge vibration is conceived. This method can accurately identify the location of bridge damage and approximately estimate the degree of bridge damage. The method is as follows: Taking the continuous beam bridge as an example, first, use the tractor inspection vehicle model to drive over the continuous beam bridge before and after the damage, and collect the acceleration response of the vehicle body. Then, the acceleration response difference is transformed by wavelet transform. Furthermore, perform the innovative use of the maximum successive approximation approach to process wavelet transform coefficients, which can identify the location of the bridge damage. Additionally, study the impact of vehicle speed, vehicle weight, road surface roughness, and noise on this damage detection method. In addition, a method for judging bridge damage degree based on wavelet transform coefficients is proposed, and the judgment error basically meets the requirements. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
ISBN:20763417 (ISSN)
DOI:10.3390/app12083743