scholarly journals Modal Parameter Identification Based on Hilbert Vibration Decomposition in Vibration Stability of Bridge Structures

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yingzhi Xia ◽  
Hui Li ◽  
Zhezhe Fan ◽  
Jiyong Xiao
Keyword(s):  
Parameter Identification ◽  
Ambient Vibration ◽  
Frequency Resolution ◽  
Response Analysis ◽  
Modal Parameter ◽  
Model Decomposition ◽  
Modal Parameter Identification ◽  
Ambient Vibration Tests ◽  
Identification Technique ◽  
Output Only

Modal parameters are important parameters for the dynamic response analysis of structures. An output-only modal parameter identification technique based on Hilbert Vibration Decomposition (HVD) is developed herein for structural modal parameter identification to (1) obtain the Free Decay Response (FDR) of a structure through free vibration or ambient vibration tests, (2) decompose the FDR into modal responses using HVD, and (3) calculate the instantaneous frequencies and instantaneous damping ratios of the modal responses to obtain the modal frequencies and modal damping ratios. A series of numerical examples are examined to demonstrate the efficiency and highlight the superiorities of the proposed method relative to the empirical model decomposition-based (EMD-based) method. The robustness of the proposed method to noises is also investigated and proved to be positive effect. The proposed method is proved to be efficient in modal parameter identification for both linear and nonlinear systems, with better frequency resolution, and it can be applied to systems with closely spaced modes and low-energy mode.

scholarly journals Comparison of Different Independent Component Analysis Algorithms for Output-Only Modal Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-25 ◽  
Author(s):  
Jianying Wang ◽  
Cheng Wang ◽  
Tianshu Zhang ◽  
Bineng Zhong
Keyword(s):  
Independent Component Analysis ◽  
Parameter Identification ◽  
Modal Analysis ◽  
Optimization Methods ◽  
Component Analysis ◽  
Independent Component ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Modal Parameters Identification ◽  
Output Only

From the principle of independent component analysis (ICA) and the uncertainty of amplitude, order, and number of source signals, this paper expounds the root reasons for modal energy uncertainty, identified order uncertainty, and modal missing in output-only modal analysis based on ICA methods. Aiming at the problem of lack of comparison and evaluation of different ICA algorithms for output-only modal analysis, this paper studies the different objective functions and optimization methods of ICA for output-only modal parameter identification. Simulation results on simply supported beam verify the effectiveness, robustness, and convergence rate of five different ICA algorithms for output-only modal parameters identification and show that maximization negentropy with quasi-Newton iterative of ICA method is more suitable for modal parameter identification.

Development and some Key Issues of Modal Parameter Identification in Bridges

2013 ◽  
Vol 574 ◽  
pp. 193-198
Author(s):  
Guo Hai Hu ◽  
Cheng Ma ◽  
Chang Xi Yang ◽  
Yang Liu
Keyword(s):  
Parameter Identification ◽  
Working Condition ◽  
Modal Identification ◽  
Modal Parameter ◽  
Fundamental Idea ◽  
Modal Parameter Identification ◽  
Identification Methods ◽  
Identification Technique ◽  
Key Issues ◽  
Ambient Excitation

In this study, the modal identification methods based on time and frequency domain are summarized, and the working condition, identified accuracy and some fundamental idea of these approaches are discussed. By comparing the characteristic of different identification method, the identification technique based on ambient excitation is promising in bridges since it is difficult to measure the excitation information. Some challenge and key issues of modal identification of bridges are pointed out in the last part.

Modal Parameter Identification of Hagia Sophia Bell-Tower via Ambient Vibration Test

2009 ◽  
Vol 28 (1) ◽  
pp. 37-47 ◽  
Author(s):  
Alemdar Bayraktar ◽  
Temel Türker ◽  
Barış Sevım ◽  
Ahmet Can Altunişik ◽  
Faruk Yildirim
Keyword(s):  
Parameter Identification ◽  
Ambient Vibration ◽  
Vibration Test ◽  
Modal Parameter ◽  
Ambient Vibration Test ◽  
Modal Parameter Identification ◽  
Bell Tower ◽  
Hagia Sophia

Consistent Multilevel RDT-ERA for Output-Only Ambient Modal Identification of Structures

2017 ◽  
Vol 17 (09) ◽  
pp. 1750106 ◽  
Author(s):  
Zhouquan Feng ◽  
Wenai Shen ◽  
Zhengqing Chen
Keyword(s):  
Parameter Identification ◽  
Modal Identification ◽  
Ambient Vibration ◽  
Weighted Averaging ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Consistency Analysis ◽  
Modal Parameter Identification ◽  
Random Decrement Technique ◽  
Random Decrement

This paper presents an improved method called the consistent multilevel random decrement technique in conjunction with eigensystem realization algorithm (RDT-ERA) for modal parameter identification of linear dynamic systems using the ambient vibration data. The conventional RDT-ERA is briefly revisited first and the problem of triggering level selection in the RDT is thoroughly studied. Due to the use of a single triggering level by the conventional RDT-ERA, an inappropriate triggering level may produce poor random decrement (RD) functions, thereby yielding a poor estimate of modal parameters. In the proposed consistent multilevel RDT-ERA, multiple triggering levels are used and a consistency analysis is proposed to sift out the RD functions that deviate largely from the majority of the RD functions. Then the ERA is applied to the retained RD functions for modal parameter identification. Subsequently, a similar consistency analysis is conducted on the identified modal parameters to sift out the outliers. Finally, the final estimates of the modal parameters are calculated using weighted averaging with the weights set proportional to the number of RD segments extracted from the corresponding triggering levels. The proposed method is featured by the fact that the information from the signal is fully utilized using multiple triggering levels and the outliers are sifted out using consistency analysis, thus making the identified result more accurate and reliable. The effectiveness and accuracy of the method have been demonstrated in the examples using the simulated data and experimental data.

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