Instantaneous Modal Parameter Identification of Linear Time-Varying Systems Based on Chirplet Adaptive Decomposition

Jie Zhang,Zhiyu Shi

doi:10.1155/2019/1475981

Abstract

Instantaneous modal parameter identification of time-varying dynamic systems is a useful but challenging task, especially in the identification of damping ratio. This paper presents a method for modal parameter identification of linear time-varying systems by combining adaptive time-frequency decomposition and signal energy analysis. In this framework, the adaptive linear chirplet transform is applied in time-frequency analysis of acceleration response for its higher energy concentration, and the response of each mode can be adaptively decomposed via an adaptive Kalman filter. Then, the damping ratio of the time-varying systems is identified based on energy analysis of component response signal. The proposed method can not only improve the accuracy of instantaneous frequency extraction but also ensure the antinoise ability in identifying the damping ratio. The efficiency of the method is first verified through a numerical simulation of a three-degree-of-freedom time-varying structure. Then, the method is demonstrated by comparing with the traditional wavelet and time-domain peak method. The identified results illustrate that the proposed method can obtain more accurate modal parameters in low signal-to-noise ratio (SNR) scenarios.

Highlights

System identification techniques have received significant attention in civil, aerospace, and mechanical engineering in the past few decades [1]
Most of them assume that the analyzed systems are linear time-invariant (LTI), i.e., the output for such systems does not change with a delay in the input
In terms of linear time-varying (LTV) system identification, many methods have been developed for various time-varying cases. ese methods generally belong to two categories: time-domain methods and time-frequency-domain methods [3]

Summary

Introduction

System identification techniques have received significant attention in civil, aerospace, and mechanical engineering in the past few decades [1]. In order to process nonstationary signals and identify the parameters of time-varying structures, many approaches were proposed based on the timedependent autoregressive moving average (TARMA) model [9]. E aim of this paper is to improve the identification accuracy of instantaneous modal parameters, i.e., instantaneous frequencies and damping ratios In these comparative examples, the Morlet wavelet and time-domain peak method are selected for comparison to identify instantaneous frequencies and damping ratios, respectively.

Theoretical Background

Instantaneous Modal Parameter Identification of Linear TimeVarying Systems

Simulation Example