A wavelet packet based sifting process and its application for structural health monitoring

Abstract

The paper presents an innovative wavelet packet based sifting process to decompose a signal into its components with different frequency content. The method is illustrated for simulation data of a linear three degree-of-freedom system and the results are compared with those using the empirical mode decomposition (EMD) method. Both methods provide good approximations for the modal responses from the modal analysis. Incorporated with the classical Hubert transform, the proposed sifting process may be effectively used for structural health monitoring, including both detecting abrupt structural stiffness loss and monitoring development of progressive stiffness degradation, as demonstrated by two case studies. Results from a preliminary study for experimental data are also presented.