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 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.

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.

Review and Prospect on Modal Parameter Identification of Spatial Lattice Structure Based on Ambient Excitation

2011 ◽  
Vol 94-96 ◽  
pp. 1271-1277
Author(s):  
Cai Wei Liu ◽  
Jin Zhi Wu ◽  
Yi Gang Zhang
Keyword(s):  
Parameter Identification ◽  
Health Monitoring ◽  
Lattice Structure ◽  
Construction Technology ◽  
Spatial Structures ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Large Span ◽  
Core Technology ◽  
Ambient Excitation

With the continuous development of national economy and the construction technology, a lot of large-span spatial structures with unique form and complex construction are emerging. The health monitoring system that mainly used in bridge structure is applied in large-span spatial structures gradually. Parameter identification and damage alarming are the core technology of health monitoring. In this paper some structural modal parameter identification methods based on ambient excitation are introduced. Finally, for large span structures with characteristics of low-intensive modes, the response data based on large span structures for modal parameter identification method was summed up, and the critical issues for further research in this field are also presented.

Software Development in Frequency Domain Modal Parameter Identification

2012 ◽  
Vol 239-240 ◽  
pp. 426-429
Author(s):  
Xin Hui Sun ◽  
Mu Ming Hao ◽  
Zhen Tao Li
Keyword(s):  
Correlation Analysis ◽  
Software Development ◽  
Parameter Identification ◽  
Modal Analysis ◽  
Narrow Band ◽  
Analysis Software ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Identification Methods ◽  
Identification Software

A modal parameter identification software named as N-Broband is developed in VC++ platform. The software is suitable for EMA and OMA with broband identification feature. Meanwhile it also includes narrow band and selected band modal parameter identification methods. Correlation analysis between experiment and FEA can be performed in N-Broband. The validation of N-Broband is carried out by Test.Lab modal analysis software. The result coincides with Test.Lab very well, which indicates that the developed software can be used in modal analysis of real structure.

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.

Frequency Domain Modal Parameter Identification of High Order Systems in a Numerically Stable Way

1997 ◽  
Vol 119 (2) ◽  
pp. 265-270 ◽  
Author(s):  
K. Q. Xu
Keyword(s):  
Parameter Identification ◽  
Frequency Domain ◽  
Narrow Band ◽  
Wide Frequency Range ◽  
Frequency Range ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Identification Methods ◽  
The Time Domain ◽  
Experimental Data Analysis

Frequency domain modal parameter identification methods have several attractive properties as compared with the time domain methods except for the limitation of low-order-and-narrow-band per analysis. As rule of thumb, a limit of less than ten modes has been observed for several popular frequency domain algorithms. However, this paper will show, that with a proper and thorough use of the orthogonal polynomials in the frequency domain, the number of modes per analysis can be increased to as high as 75 in a comparatively wide frequency range of interest while still retaining numerical stability. Both numerical example (75 modes in 5–1000 Hz) and experimental data analysis (56 modes in 50–5000 Hz) are presented to demonstrate the effectiveness of this innovative approach.

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.

Sign in / Sign up

Export Citation Format

Share Document