Structural Modal Parameter Identification of the Bridge Subject to Environment Excitation

2013 ◽  
Vol 482 ◽  
pp. 136-140
Author(s):  
Yan Chen ◽  
Can Ying Huang ◽  
Shu Yun Zhu
Keyword(s):  
Power Spectrum ◽  
Measurement Method ◽  
Function Analysis ◽  
Coherence Function ◽  
Measurement Data ◽  
Phase Information ◽  
Modal Parameter ◽  
Reliable Measurement ◽  
Modal Parameter Identification ◽  
Identification Methods

Experiments were performed on Jundu Mountain Aqueduct Bridge, the article introduces the identification methods and processes which obtain modal parameter of bridge subject to Environment excitation. Layout of points effectively by moving the measurement method can obtain reliable measurement data, and it uses self-power spectrum、cross power spectrum and coherence function analysis , With the use of analytic technology for spectrum, has identified the preceding six natural frequency of the bridge vibration and has analyzed the phase information of he bridge vibration.

Research on Modal Parameter Identification of the Cable Stayed Bridges Based on the Singular Value Decomposition of the Power Spectrum

2012 ◽  
Vol 256-259 ◽  
pp. 1623-1626
Author(s):  
Hong Xia Xiong ◽  
Ci Feng Qin ◽  
Yang Jiang
Keyword(s):  
Singular Value Decomposition ◽  
Power Spectrum ◽  
Parameter Identification ◽  
Singular Value ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Element Computation ◽  
Modal Selection ◽  
Value Decomposition ◽  
Selection Of

In view of the modal parameter identification when only has the output signals of the system under ambient excitations has difficulty, a new method which can identify the structural modal parameters exactly based on singular value decomposition of the power spectrum is put forward. This method is used in the modal parameter identification of a cable stayed bridge under ambient excitations, and the identification frequency is compared with the finite element computation frequency. The results indicated that this method has overcome the subjectivity in modal selection of frequency domain pick-peaking method, choose eigenfrequency and identify close modal accurately and objectively. With the advantages of practical, processing simply and fast.

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.

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.

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.

Quantum-Behaved Particle Swarm Optimization-Based Structural Modal Parameter Identification Under Ambient Excitation

2016 ◽  
Vol 16 (05) ◽  
pp. 1550008 ◽  
Author(s):  
Jun Chang ◽  
Satish Nagarajaiah
Keyword(s):  
Particle Swarm Optimization ◽  
Power Spectrum ◽  
Parameter Identification ◽  
Particle Swarm ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Swarm Optimization ◽  
Modal Parameter Identification ◽  
Ambient Excitation ◽  
Cross Power Spectrum

Under ambient excitation of white noise, structural modal parameters can be identified from cross-power spectrum calculated from structural outputs, without known input. The minimization of difference between theoretical value and test value of cross-power spectrum — the former is an equation including modal parameters to be identified, and the latter is computed based on the output-only data of structure — is adopted as an objective function for optimization. The optimal objective function value can be obtained through optimal modal parameter search. Quantum-behaved particle swarm optimization (QPSO) — swarm intelligence optimization algorithm based on particle swarm optimization (PSO) — is used for optimization to identify the modal parameters of structure under the ambient excitation. Then, the modal parameter identification method based on QPSO presented herein had been demonstrated by a numerical simulation of three-span continuous beam and experimental results of a three story structure. The computed results indicated that QPSO can be effectively used in the structural modal parameter identification under ambient excitation.

A Review on Damage Identification and Structural Health Monitoring for Offshore Platform

2016 ◽  
Author(s):  
Liping Sun ◽  
Yang Lu ◽  
Xinyue Zhang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Identification ◽  
Offshore Platform ◽  
Statistical Pattern Recognition ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Identification Methods ◽  
Structural Health ◽  
Statistical Pattern

Structural health monitoring (SHM) based on vibration measurements in large/complex structures were shown to be promising by researchers. The authors believe that the SHM problem is fundamentally one of statistical pattern recognition. Therefore, the damage detection studies reviewed herein are summarized in the context of a statistical pattern recognition paradigm[1]. This paradigm can be described as a three-part process: (1) Data acquisition and cleansing, (2) Modal parameter identification, (3) Damage identification methods. However, offshore platform structures are very complex, and not easy to excite artificially and they are often suffered from ambient loads that cannot be controlled easily. The thesis focuses on three key issues for structural health monitoring via vibration in real offshore platform structures[2]. In the first part of review, the offshore platform structure health monitoring system basic principle and the composition are discussed. In the second portion, three important processes of structure health monitoring are summarized (Data acquisition and cleansing, modal parameter identification, damage identification methods), and each method good and bad points is pointed out. Next, Application of damage identification and structural health monitoring to offshore platform are in detail produced, the methods are described in general terms including difficulties associated with their implementation. Finally, current and future-planned applications of this technology to offshore platform are summarized. The paper concludes with a discussion of critical issues for future research on damage identification and structural health monitoring for offshore platform.

A Study on Structural System Identification and Damage Detection for Free Vibration Response Using the Wavelet Transform

2015 ◽  
Vol 752-753 ◽  
pp. 1029-1034
Author(s):  
Asnizah Sahekhaini ◽  
Pauziah Muhamad ◽  
Masayuki Kohiyama ◽  
Aminuddin Abu ◽  
Lee Kee Quen ◽  
...  
Keyword(s):  
Free Vibration ◽  
Damage Detection ◽  
Vibration Response ◽  
Structural System ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Complex Morlet Wavelet ◽  
Structural System Identification ◽  
Free Vibration Response ◽  
Energy Components

This paper presents a wavelet-based method of identification modal parameter and damage detection in a free vibration response. An algorithm for modal parameter identification and damage detection is purposed and complex Morlet wavelet is chosen as an analysis wavelet function. This paper only focuses on identification of natural frequencies of the structural system. The method utilizes both undamaged and damage experiment data of free vibration response of the truss structure system. Wavelet scalogram is utilizes for damage detection. The change of energy components for undamaged and damage structure is investigated from the plot of wavelet scalogram which corresponded to the detection of damage.

Detection and Analysis of Rats’ Bioelectromagnetic Signal

2014 ◽  
Vol 536-537 ◽  
pp. 13-17
Author(s):  
Hong Long Cao ◽  
Fen Ju Qin ◽  
Xue Guan Liu ◽  
He Ming Zhao
Keyword(s):  
Standard Deviation ◽  
Automatic System ◽  
Measurement Method ◽  
Measurement Accuracy ◽  
Biological Activities ◽  
Measurement Data ◽  
Measured Data ◽  
The Mean ◽  
Frequency Window ◽  
Window Effects

In this paper, we designed an automatic system and automatic test software, and they can carry out Kunming rats bioelectromagnetic measurement in standard status and anesthesia automatically in anechoic chamber where the electromagnetic field outside is shielded, the reflection wave is absorbed, and the measurement accuracy will be improved. We get a great number of measurement data with frequency-sweep measurement method. The mean and standard deviation of amplitudes vs. frequencies is calculated and analyzed. The results show the measurement method is feasible. We have plotted the means of measured data as multiple sets of Y values in a series of bars with standard deviations bars included and distributed in the frequency axis of X. It is found that the fluctuation of the mean and standard deviation in some frequencies is not evident which may explain frequency window effects, while in other frequencies, such a fluctuation can be obviously observed, which may suggest that bioelectromagnetic signal is influenced by biological activities (standard and anaesthesia status) in these frequency points.

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