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Structural Monitoring and Maintenance
  Volume 7, Number 2, June 2020, pages 149-166
DOI: http://dx.doi.org/10.12989/smm.2020.7.2.149
 


Damage detection of railway bridges using operational vibration data: theory and experimental verifications
Md Riasat Azim, Haiyang Zhang and Mustafa Gül 

 
Abstract
    This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.
 
Key Words
    damage identification; experimental investigation; railway bridges; time-series analysis; operational acceleration response
 
Address
Md Riasat Azim: Department of Civil & Environmental Engineering, University of Alberta, Natural Resources Engineering Facility 5-090, 9105 116 Street NW, Edmonton, Alberta, T6G 2W2, Canada
Haiyang Zhang: Department of Civil & Environmental Engineering, University of Alberta, Natural Resources Engineering Facility 5-042, 9105 116 Street NW, Edmonton, Alberta, T6G 2W2, Canada
Mustafa Gül: 3Department of Civil & Environmental Engineering, University of Alberta, Donadeo Innovation Centre for Engineering 7-257, 9211 116 Street NW, Edmonton, Alberta, T6G 1H9, Canada
 

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