Structural damage detection with canonical correlation analysis using limited sensors

This paper presents a novel structural damage detection method using limited sensors for beam bridge subjected to a moving mass. In this method, the measured acceleration responses are cut out by a moving window with a length determined by the sampling frequency and the funda-mental frequency of the bridge. The windowed responses are processed by the subspace analysis to extract the principal components. The correlation coefficients between the principal compo-nents in the window are obtained using the canonical correlation analysis (CCA). Finally, a new damage factor in the window is defined based on the output of the CCA. Moving the window, a time series of the damage factor is obtained. When the moving mass passes through the damage location of the bridge, the curve of the damage factor has a peak that the damage can be iden-tified. To demonstrate the proposed method, a beam bridge is numerically modelled and a simply supported beam bridge model is tested in the lab. Both the numerical and experimental results demonstrate that this method can successfully identify the single and multiple damages with a limited number of sensors.

Automated summary

This paper presents a novel method for structural damage detection in beam bridges using limited sensors. The method involves cutting out measured acceleration responses with a moving window, extracting principal components through subspace analysis, and obtaining correlation coefficients between the components using canonical correlation analysis. A new damage factor is defined based on the output of the correlation analysis. Numerical and experimental results demonstrate the successful identification of single and multiple damages using a limited number of sensors.