Enhanced vibration decomposition method based on multisynchrosqueezing transform and analytical mode decomposition

Abstract

This paper proposes an enhanced vibration decomposition approach based on analytical mode decomposition (AMD) and multisynchrosqueezing transform (MSST). Although AMD-based low-pass filter has been applied for signal decomposition with time-varying cutoff frequencies, these cutoff frequencies are usually manually selected from the wavelet scalogram of the target signal. This process therefore significantly reduces the computational efficiency and could affect the accuracy of using AMD-based low-pass filter for non-stationary signal analysis. To overcome this problem, in this study, MSST with a time-varying cutoff frequency detection algorithm is used to automatically define the time-varying bisecting frequencies for the AMD analysis. Once the time-varying cutoff frequencies are identified, AMD can be used to adaptively decompose the non-stationary signal into individual components. To investigate the effectiveness of the proposed approach, termed as MSST–AMD, for vibration signal decomposition and its application, numerical studies on a non-stationary signal with overlapped frequency components are conducted. To further apply the proposed approach for structural vibration response analysis, a three-story shear-type structure with varying stiffness subjected to earthquake excitations is simulated in this study for instantaneous modal parameter identification. In experimental verifications, the proposed MSST–AMD approach combined with a damage index is further extended to evaluate the damage severity of a structure under earthquake excitations. The results in both numerical simulations and experimental validations demonstrate that the proposed approach is reliable and accurate for non-stationary signal analysis and vibration decomposition, which can be further used for instantaneous modal parameter identification and structural damage detection.