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.

scholarly journals Noise Reduction for Modal Parameter Identification of the Measured FRFs Using the Modal Peak-Based Hankel-SVD Method

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Tianxu Zhu ◽  
Chaoping Zang ◽  
Gengbei Zhang
Keyword(s):  
Parameter Identification ◽  
Noise Reduction ◽  
Flat Plate ◽  
Modal Identification ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Noise Elimination ◽  
Modal Parameter Identification ◽  
Modal Test ◽  
Svd Method

The measured frequency response functions (FRFs) in the modal test are usually contaminated with noise that significantly affects the modal parameter identification. In this paper, a modal peak-based Hankel-SVD (MPHSVD) method is proposed to eliminate the noise contaminated in the measured FRFs in order to improve the accuracy of the identification of modal parameters. This method is divided into four steps. Firstly, the measured FRF signal is transferred to the impulse response function (IRF), and the Hankel-SVD method that works better in the time domain rather than in the frequency domain is further applied for the decomposition of component signals. Secondly, the iteration of the component signal accumulation is conducted to select the component signals that cover the concerned modal features, but some component signals of the residue noise may also be selected. Thirdly, another iteration considering the narrow frequency bands near the modal peak frequencies is conducted to further eliminate the residue noise and get the noise-reduced FRF signal. Finally, the modal identification method is conducted on the noise-reduced FRF to extract the modal parameters. A simulation of the FRF of a flat plate artificially contaminated with the random Gaussian noise and the random harmonic noise is implemented to verify the proposed method. Afterwards, a modal test of a flat plate under the high-temperature condition was undertaken using scanning laser Doppler vibrometry (SLDV). The noise reduction and modal parameter identification were exploited to the measured FRFs. Results show that the reconstructed FRFs retained all of the modal features we concerned about after the noise elimination, and the modal parameters are precisely identified. It demonstrates the superiority and effectiveness of the approach.

Modal Parameter Identification of a Rigid Frame-Continuous Girders Bridge under Ambient Excitation by Fast Bayesian FFT Method

2013 ◽  
Vol 639-640 ◽  
pp. 985-991 ◽  
Author(s):  
Jian Ping Han ◽  
Pei Juan Zheng
Keyword(s):  
Parameter Identification ◽  
Model Updating ◽  
Element Model ◽  
Modal Identification ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Stochastic Subspace Identification ◽  
Rigid Frame ◽  
Ambient Excitation

Bayesian theory is adopted in modal parameter identification, finite element model updating and residual capacity evaluation of the structures recently. Fast Bayesian FFT modal identification approach provides a rigorous way to obtain modal parameters and well-separated modes using the fast Fourier transform under ambient excitation. Moreover, it avoids choosing the modal order or removing false modes based on the stable diagram and has its obvious advantages. In this paper, modal parameters of a rigid frame-continuous girders bridge under ambient excitation are identified by this approach. Comparison with stochastic subspace identification (SSI) method indicates that Fast Bayesian FFT is a good approach to identify the modal parameters even for a large number of measurement channels.

Study of Modal Parameter Identification from Ambient Vibration on a Deep Radial Gate

2011 ◽  
Vol 105-107 ◽  
pp. 511-517
Author(s):  
Yuan Qi Cai ◽  
Ke Zhang
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Damping Ratio ◽  
Modal Identification ◽  
Ambient Vibration ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Flood Discharge ◽  
Prototype Test ◽  
Radial Gate

In the engineering background of the prototype test of a deep radial gate on three gorges dam, two methods are provided for the modal parameter identification of the radial gate, one is applying operation modal analysis (OMA) to a gate which is under flood discharge, the other one is applying experiment modal analysis (EMA) to a inactive gate with some other gates under flood discharge. This paper is based on the feasibility study on the former method. We use the natural excitation technology (NExT) combined with the eigensystem realization algorithm (ERA) to determine the dynamic characteristics of a gate. Displacement data at 7 locations were processed using NExT-ERA to extract the natural frequency and associated damping ratio. The results show the effectiveness of this modal identification methodology and the possibility of implementing it on other hydraulic structure.

Methods of Gear Damage Assessment Based on Modal Parameter Identification

2013 ◽  
Vol 819 ◽  
pp. 38-42
Author(s):  
Jin Bao Ma ◽  
Jian Yu Zhang ◽  
Xin Bo Liu
Keyword(s):  
Parameter Identification ◽  
Damage Assessment ◽  
Spur Gear ◽  
Modal Parameters ◽  
Vibration Characteristic ◽  
Modal Parameter ◽  
Damage State ◽  
Element Analysis ◽  
Modal Parameter Identification ◽  
Vibration Mechanism

With the evolution and degradation of mechanical fault, changes of the structural inherent characteristics will directly affect the overall response of system. Spur gear, which worked as the research object, is to be explored on the changes of modal parameters under different damage state. Optimum driving-point mobility and modal parameter identification is achieved by comprehensive utilization of experimental modal analysis and finite element analysis. is used to determine the experiment results is whether accurate or not. Then comparing with the differences of modal parameters, the preliminary judgment of gear damage can be made. According to the experimental data of different gears, theis taken to complete the correlation analysis and to judge the degree of the damage. The results shows that provide an effective basis for the identification of vibration mechanism and vibration characteristic of fault gear.

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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