1 April 2016 Damage detection based on mode shapes of a girder bridge constructed from responses of a moving vehicle under impact excitation
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The vibration mode shapes are often used to identify damage of bridges because the mode shapes are not only important modal properties but also sensitive to damage. However, the key issue is how to conveniently obtain the mode shapes of a bridge in service. Traditional methods invariably require installation of instruments on the bridge for collection of dynamic responses for constructing mode shapes, which are both costly and inconvenient. Therefore a method is developed to construct the mode shapes of simply supported bridges based on Hilbert Transform using only vehicle acceleration response for identification of the location of damage. Firstly, an algorithm is devised to construct the mode shapes by using the dynamic responses extracted from a moving vehicle under impact excitation. Then, based on these intermediate results, the coordinate modal assurance criterion in conjunction with suitable wavelets is used to identify the location of damage. Compared with the traditional methods, the proposed method uses only the information from the moving vehicle. Moreover, additional impact excitation on the vehicle helps to excite the bridge. This helps to improve the accuracy by overcoming the adverse effects of measurement noise and road surface roughness, which leads to high accuracy of damage detection. To verify the feasibility of the proposed method, some numerical studies have been carried out to investigate the effects of measurement noise, road surface roughness and multiple locations of damage on the accuracy of results.
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Zhongqiang Qi, Zhongqiang Qi, Francis T. K. Au, Francis T. K. Au, "Damage detection based on mode shapes of a girder bridge constructed from responses of a moving vehicle under impact excitation", Proc. SPIE 9805, Health Monitoring of Structural and Biological Systems 2016, 980507 (1 April 2016); doi: 10.1117/12.2218428; https://doi.org/10.1117/12.2218428

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