Continuous condition assessment for bridges based on wavelet packets decomposition

Wavelets analysis is a mathematical tool that can represent a signal in terms of basis functions and thus can describe the signal on various levels of resolutions or scales corresponding to different frequency bands. They have advantages over traditional Fourier methods in analyzing nonstationary signal. In this study, a method based on wavelet packet decomposition (WPD) is proposed to process vibration signals of a structure that undergoes characteristic changes due to damage. The method decomposes the vibration signals into a data set with various levels of resolutions, hence small changes caused by structural damage become visible in some levels. The wavelet packets are used since they can produce narrower and more improved frequency resolutions as compared to the original wavelet. Based on this decomposition, component energy indices are chosen as indicators for structure health condition assessment. For illustration, a numerical simulation is performed on a three-span continuous bridge deck with different characteristic changes under impact loads. The case study shows that the component energy indices obtained from the WPD are excellent indicators for structure health condition assessment. When they are fed into well-trained neural network classifiers, structural conditions such as damage occurrence, location and severity can be identified quite accurately