Synchrosqueezing transform-based identification of time-varying structural systems using multi-sensor data

Abstract

In this paper, a hybrid time-frequency method combining Synchrosqueezing Transform (SST) and Multivariate Empirical Mode Decomposition (MEMD) is proposed for the identification of time-varying structural systems. MEMD is first used to decompose the closely spaced modal responses of structures into mono components, and SST is then used to track time-varying modal frequencies with a better time-frequency resolution, thereby improving the capability of both methods. A single degree-of-freedom model is first used to study the sensitivity for damage duration and frequency resolution of the SST under measurement noise. The proposed method is then validated using a multi-degree-of-freedom simulation model, an experimental model, and a full-scale study using MIT Green Building data. The results show that the proposed method has successfully identified time-varying frequencies of various types of structures under different extent of measurement noise.