Modal parameter identification of time-varying systems via wavelet-based frequency response function

2020 ◽  
Vol 90 (11) ◽  
pp. 2529-2542
Author(s):  
Lijie Zhao ◽  
Dongli Jin ◽  
Hao Wang ◽  
Chengqing Liu
Keyword(s):  
Parameter Identification ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Time Varying ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Time Varying Systems

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.

Frequency response function-based parameter identification from short data sequences

2004 ◽  
Vol 18 (5) ◽  
pp. 1097-1116 ◽  
Author(s):  
B. Cauberghe ◽  
P. Guillaume ◽  
P. Verboven ◽  
S. Vanlanduit ◽  
E. Parloo
Keyword(s):  
Parameter Identification ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function

scholarly journals Parameter Identification of Weakly Nonlinear Vibration System in Frequency Domain

2004 ◽  
Vol 11 (5-6) ◽  
pp. 685-692 ◽  
Author(s):  
Jiehua Peng ◽  
Jiashi Tang ◽  
Zili Chen
Keyword(s):  
Parameter Identification ◽  
Frequency Response ◽  
Nonlinear Vibration ◽  
Frequency Domain ◽  
Response Function ◽  
Frequency Response Function ◽  
Physical Parameters ◽  
Vibration System ◽  
Weakly Nonlinear ◽  
Nonlinear Vibration System

A new method of identifying parameters of nonlinearly vibrating system in frequency domain is presented in this paper. The problems of parameter identification of the nonlinear dynamic system with nonlinear elastic force or nonlinear damping force are discussed. In the method, the mathematic model of parameter identification is frequency response function. Firstly, by means of perturbation method the frequency response function of weakly nonlinear vibration system is derived. Next, a parameter transformation is made and the frequency response function becomes a linear function of the new parameters. Then, based on this function and with the least square method, physical parameters of the system are identified. Finally, the applicability of the proposed technique is confirmed by numerical simulation.

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.

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