A Wavelet Packet Based Sifting Process and its Application for Structural Health Monitoring

This article presents an innovative wavelet packet based sifting process to decompose a signal into its components with different frequency contents by examining the energy content in the wavelet packet components of a signal and imposing certain decomposition criteria. A new method is illustrated for simulation data of a linear three-degree-of-freedom spring-mass-damper system and the results are compared with those obtained using the empirical mode decomposition (EMD) method. Both methods provide good approximations, as compared with the exact solution for modal responses from a conventional modal analysis and both show relatively greater errors at the beginning and ending parts of the signal due to the well-known end effects. A comparison study is also provided to illustrate differences between two sifting processes of the proposed approach and the EMD, by using a harmonic signal with a sweeping frequency and the impulse response of a linear single-degree-of-freedom system with viscous damping. Incorporated with the classical Hilbert transform, the proposed sifting process may be effectively used for structural health monitoring, including both detecting abrupt loss of structural stiffness and monitoring development of progressive stiffness degradation, as demonstrated by two case studies. Results from a preliminary study for experimental data from a shaking table test of a full-size two-story wooden building structure are also presented to show great promise of the proposed method in practical applications of health monitoring of real structures.