Adaptive window function and window size based operational modal parameter identification for linear time-varying structure

2020 ◽  
Vol 64 (1-4) ◽  
pp. 517-524
Author(s):  
Haiyang Huang ◽  
Cheng Wang ◽  
Xiongming Lai ◽  
Jianwei Chen
Keyword(s):  
Parameter Identification ◽  
Principle Component Analysis ◽  
Window Size ◽  
Window Function ◽  
Time Varying ◽  
Moving Window ◽  
Response Signal ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Principle Component

In order to select the window function and window size adaptively before getting the results, we proposed adaptive moving window principle component analysis (AMWPCA) based OMA method to identify modal shapes and modal natural frequencies of slow LTV structures with weekly damped only from non-stationary vibration response signal online. The adaptive is achieved in two ways: change the window function or window size. We develop an adaptive indicator as the basis for window function and window size changes. Our adaptive approach is to make the difference between adjacent eigenvalues not too small. The operational modal parameter identification results in non-stationarity response signal dataset of a three-degree-of-freedom structure with slow time-varying mass show that comparing with fixed size moving window principle component analysis, our AMWPCA method can identify the modal shapes and modal frequencies better.

scholarly journals Time-Varying Modal Parameters Identification by Subspace Tracking Algorithm and Its Validation Method

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Haotian Zhou ◽  
Kaiping Yu ◽  
Yushu Chen ◽  
Rui Zhao ◽  
Yunhe Bai
Keyword(s):  
Parameter Identification ◽  
Spatial Clustering ◽  
Signal To Noise Ratio ◽  
Information Criterion ◽  
Modal Parameters ◽  
Identification Algorithm ◽  
Time Varying ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Post Process

This article presents a time-varying modal parameter identification method based on the novel information criterion (NIC) algorithm and a post-process method for time-varying modal parameter estimation. In the practical application of the time-varying modal parameter identification algorithm, the identified results contain both real modal parameters and aberrant ones caused by the measurement noise. In order to improve the quality of the identified results as well as sifting and validating the real modal parameters, a post-process procedure based on density-based spatial clustering of applications with noise (DBSCAN) algorithm is introduced. The efficiency of the proposed approach is first verified through a numerical simulation of a cantilever Euler-Bernoulli beam with a time-varying mass. Then the proposed approach is experimentally demonstrated by composite sandwich structure in a time-varying high temperature environment. The identified results illustrate that the proposed approach can obtain real modal frequencies in low signal-to-noise ratio (SNR) scenarios.

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

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Jie Zhang ◽  
Zhiyu Shi
Keyword(s):  
Parameter Identification ◽  
Energy Analysis ◽  
Linear Time ◽  
Damping Ratio ◽  
Energy Concentration ◽  
Time Varying ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Time Frequency ◽  
Time Varying Systems

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.

Modal Parameter Identification of Time-Varying Systems Using the Time-Varying Multivariate Autoregressive Model

2005 ◽  
Author(s):  
Lilan Liu ◽  
Hongzhao Liu ◽  
Ziying Wu ◽  
Daning Yuan ◽  
Pengfei Li
Keyword(s):  
Parameter Identification ◽  
Linear Time ◽  
Damping Ratio ◽  
Least Square Method ◽  
Least Square ◽  
Time Varying ◽  
Recursive Least Square ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Multivariate Autoregressive

A new time-varying multivariate autoregressive (TVMAR) model method for modal parameter identification of linear time-varying (TV) systems with multi-output is introduced. Besides, a modified recursive least square method based on the traditional one is presented to determine the coefficient matrices of the TVMAR model. In the proposed method, multi-dimensional nonstationary response signals of the vibrating system can be processed simultaneously. Not only the TV modal frequency and damping ratio of the system, but also the changing behavior of the mode shape in the course of vibration are identified by the proposed procedure. Numerical simulations, in which a three-degree-of-freedom system with TV stiffness is respectively subjected to impulse excitation and white noise excitation, are presented. The validity and accuracy of the method are demonstrated by the good simulation results.

HHT-Based Modal Parameter Identification of Time-Varying Structures and Experiment Study

2011 ◽  
Vol 243-249 ◽  
pp. 5444-5449 ◽  
Author(s):  
Xue Min Wang ◽  
Fang Lin Huang
Keyword(s):  
Parameter Identification ◽  
Degrees Of Freedom ◽  
Modal Parameters ◽  
Time Varying ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Hilbert Huang Transform ◽  
Mode Decomposition ◽  
Continuous Mass ◽  
Stiffness And Damping

A method for modal parameter identification of time-varying structures based on Hilbert- Huang transform (HHT) is presented. Theoretical formulas for identifying the modal frequency and damping radio using the displacement response of a time-varying SDOF structure are deduced. Taking advantage of modal filtering characteristics of empirical mode decomposition (EMD), the presented method is expanded to identify the modal parameters of MDOF structures. Numerical simulation of a three degrees of freedom structure with time-varying stiffness and damping show the validity of the method. Finally, a time-varying structure experiment is designed to further study the method. The experimental device is a cantilever beam. By adjusting the adjunctive mass and stiffness, two kinds of time-varying structures with continuous mass change and stiffness change is realized respectively. Modal parameters are identified from the free acceleration response of the beam.

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