Moving Window Differential Evolution Independent Component Analysis-Based Operational Modal Analysis for Slow Linear Time-Varying Structures

Yongshuo Zong,Jinling Chen,Siyi Tao,Cheng Wang,Jianbing Xiahou,Chenxi Huang

doi:10.1155/2020/8879086

Yongshuo Zong, Jinling Chen + Show 4 more

Open Access

https://doi.org/10.1155/2020/8879086

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Journal: Scientific programming	Publication Date: Nov 23, 2020
Citations: 1	License type: CC BY 4.0

Affiliation: Xiamen University, Huaqiao University

Abstract

In order to identify time-varying transient modal parameters only from nonstationary vibration response measurement signals for slow linear time-varying (SLTV) structures which are weakly damped, a moving window differential evolution (DE) independent component analysis- (ICA-) based operational modal analysis (OMA) method is proposed in this paper. Firstly, in order to overcome the problems in traditional ICA-based OMA, such as easy to go into local optima and difficult-to-identify high-order modal parameters, we combine DE with ICA and propose a differential evolution independent component analysis- (DEICA-) based OMA method for linear time invariant (LTI) structures. Secondly, we combine the moving widow technique with DEICA and propose a moving window differential evolution independent component analysis- (MWDEICA-) based OMA method for SLTV structures. The MWDEICA-based OMA method has high global searching ability, robustness, and complexity of time and space. The modal identification results in a three-degree-of-freedom structure with slow time-varying mass show that this MWDEICA-based OMA method can identify transient time-varying modal parameters effectively only from nonstationary vibration response measurement signals and has better performances than moving window traditional ICA-based OMA.

Highlights

It is hoped that the engineering structure will have a high degree of self-adaptive or self-control ability, and it can automatically change its shape and performance to adapt to changes in environmental disturbances and new usage requirements as the environment or use functions change
Operational Modal Analysis (OMA) can estimate modal parameters without input data, which is not easy to obtain in large-scale engineering structures [1]. e modal parameters of a linear time-varying structure can reflect the overall dynamics of the structure [2]
Based on the moving window [24] and independent component analysis [15], this paper presents a moving window differential evolution independent component analysis- (MWDEICA-) based OMA method for weakly damped slow linear time-varying (SLTV) structures

Summary

Introduction

It is hoped that the engineering structure will have a high degree of self-adaptive or self-control ability, and it can automatically change its shape and performance to adapt to changes in environmental disturbances and new usage requirements as the environment or use functions change. Because its optimization method is easy to go into local optima, traditional ICA-based OMA has low robustness, and it is difficult to identify high-order modal parameters using that [14]. (1) In this paper, we propose a new DEICA-based OMA method to identify modal parameters only from stationary random response signals for LTI structures. Using DE algorithm to replace the traditional linear regression optimization algorithm to search the separation matrix, the DEICA-based OMA method has high global searching ability, robustness, and complexity of time and space. Compared with the traditional ICA method based on gradient optimization algorithm, OMA based on DEICA can identify higher-order modal parameters and has high recognition accuracy. Is method can effectively identify the transient time-varying modal parameters only from the nonstationary random response measurement signals, which is better than the traditional moving window method.

Theoretical Inference of Algorithm

Simulation Identification

Conclusions