Single point mooring system modal parameter identification based on empirical mode decomposition and time-varying autoregressive model

2015 ◽  
Vol 53 ◽  
pp. 250-256 ◽  
Author(s):  
Da Tang ◽  
Chuanchuan Xu ◽  
Qianjin Yue ◽  
Wenhua Wu ◽  
Zhongmin Shi ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Empirical Mode Decomposition ◽  
Autoregressive Model ◽  
Single Point ◽  
Mooring System ◽  
Time Varying ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Mode Decomposition

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.

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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