An Improved Time-Domain Damage Detection Method for Railway Bridges Subjected to Unknown Moving Loads

Authors

  • Mahdi Shahbaznia
    Affiliation
    School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran 16846-13114, Iran
  • Morteza Raissi Dehkordi
    Affiliation
    School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran 16846-13114, Iran
  • Akbar Mirzaee
    Affiliation
    School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran 16846-13114, Iran
https://doi.org/10.3311/PPci.15813

Abstract

There is considerable interest in structural health monitoring (SHM) and damage detection of bridges and considerable progress has been made in this field in recent years. However, several challenges such as sensitivity to low levels of damage and identification without the knowledge of the moving load remain and need to be precisely investigated by researchers. The current work addresses such challenges and proposes an efficient response sensitivity-based model updating procedure in time-domain for damage identification of railway bridges subjected to unknown moving loads. The bridge is modelled as an Euler-Bernoulli beam and the train is modelled as a set of sprung masses passing over the beam. Structural damage is considered as a reduction in the modulus of elasticity of the elements. Sensitivity analysis and Tikhonov regularization methods are adopted and used to solve the inverse problem of the model updating. To verify the efficiency of the model, two numerical models with multiple damage scenarios subjected to unknown moving loads are analyzed. In addition, the efficiency of the proposed method in the presence of measurement noise is also verified. Numerical results reveal that the proposed model-updating procedure simultaneously identifies structural damages as well as the unknown moving loads with an acceptable accuracy. The effect of critical parameters such as mass and speed of the moving vehicle on the accuracy of identification results is investigated as well. Based on the findings of this research, the proposed method can be adopted and applied to online and long-term health monitoring of real bridge structures.

Keywords:

railway bridge, model-updating, damage detection, sensitivity analysis, unknown input, time-domain

Citation data from Crossref and Scopus

Published Online

2020-07-13

How to Cite

Shahbaznia, M., Raissi Dehkordi, M., Mirzaee, A. “An Improved Time-Domain Damage Detection Method for Railway Bridges Subjected to Unknown Moving Loads”, Periodica Polytechnica Civil Engineering, 64(3), pp. 928–938, 2020. https://doi.org/10.3311/PPci.15813

Issue

Section

Research Article