Wavelet-based signal analysis technique and its application to real-time signal processing of structural health monitoring

Wavelet transform is a robust mathematical tool for signal analysis, which has the capability of showing local character of signal in time domain and frequency domain. Using the multi-resolution ability of wavelet analysis and Lipschitz exponent, we can separate noise signal into several detail signals and approximation signal distinguishing from the traditional method. At the same time, with the help of wavelet packet analysis, the energy distribution eigenvector of structural response can be obtained. Based on the structural health monitoring (SHM) system of Nanjing Yangtze river bridge (NYRB), the multi-resolution information express of real-time monitoring signals was obtained, the noise of real-time monitoring signal was eliminated and the energy distribution eigenvector under different conditions were obtained by wavelet and wavelet packet analysis, which can enrich our cognition of character reflected by signals and help us to exactly distinguish the structure condition. These results demonstrate that wavelet-based signal analysis technique is a useful tool for real-time monitoring signal processing.