Bridge damage detection using PCA-DWT with limited sensors

Traditional bridge detection methods require a large number of sensors, which restricts the application in practical engineering. In order to reduce the cost of the health monitoring system and improve the accuracy of bridge damage detection, a bridge damage detection method based on principal component analysis and discrete wavelet transform is proposed. This method performs principal component analysis on the displacement under moving load and obtains the first principal component composed of dynamic component and modal shape. The first principal component is separated by the low-pass filter to receive the dynamic component of the first mode. Then the dynamic component is analyzed by the discrete wavelet transform to obtain the wavelet coefficient. Then the wavelet coefficient is used to reconstruct the signal. Finally, damage index is defined by using the reconstructed signal to detect the damage. When the structure is damaged, the damage index peaks at the damage location. In order to verify the effectiveness of the method, a beam bridge is simulated and a steel beam bridge is tested in the laboratory. Both simulation and experimental results show the proposed method can accurately identify the damage location in various scenarios with limited sensors.