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.

Modal Parameter Identification of 500kV SF6 Current Transformer Based on Natural Excitation Method

2014 ◽  
Vol 1065-1069 ◽  
pp. 3400-3405
Author(s):  
Qian Zhang ◽  
Zhi Cheng Lu ◽  
Yu Han Sun ◽  
Min Zhong
Keyword(s):  
Correlation Function ◽  
Parameter Identification ◽  
Modal Analysis ◽  
Cross Correlation ◽  
Impulse Response Function ◽  
Current Transformer ◽  
Cross Correlation Function ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Excitation Method

In this paper the feasibility of natural excitation method which uses cross-correlation function instead of impulse response function of the response to identify the modal parameter of 500kV SF6 current transformer was discussed .Four different algorithms were used to extract the modal parameter of 500kV SF6 current transformer with the measured cross-correlation function obtained by natural excitation method. The results of modal parameter identification using natural excitation method and experimental modal analysis were compared in the experimental way.

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.

Identify Modal Parameters of a Real Offshore Platform From the Response Excited by Natural Ice Loading

2016 ◽  
Author(s):  
Wenlong Yang ◽  
Lei Li ◽  
Qiang Fu ◽  
Yao Teng ◽  
Shuqing Wang ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Offshore Platform ◽  
Operational Modal Analysis ◽  
Modal Parameters ◽  
Offshore Platforms ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Stability Diagrams ◽  
The Stability

Experimental modal analysis (EMA) is widely implemented to obtain the modal parameters of an offshore platform, which is crucial to many practical engineering issues, such as vibration control, finite element model updating and structural health monitoring. Traditionally, modal parameters are identified from the information of both the input excitation and output response. However, as the size of offshore platforms becomes huger, imposing artificial excitation is usually time-consuming, expensive, sophisticated and even impossible. To address this problem, a preferred solution is operational modal analysis (OMA), which means the modal testing and analysis for a structure is in its operational condition subjected to natural excitation with output-only measurements. This paper investigate the applicability of utilizing response from natural ice loading for operational modal analysis of real offshore platforms. The test platform is the JZ20-2MUQ Jacket platform located in the Bohai Bay, China. A field experiment is carried out in winter season, when the platform is excited by floating ices. An accelerometer is installed on a leg and two segments of acceleration response are employed for identifying the modal parameters. In the modal parameter identification, specifically applied is the data-driven stochastic sub-space identification (SSI-data) method. It is one of the most advanced methods based on the first-order stochastic model and the QR algorithm for computing the structural eigenvalues. To distinguish the structural modal information, stability diagrams are constructed by identifying parametric models of increasing order. Observing the stability diagrams, the modal frequencies and damping ratios of four structural modes can be successfully identified from both segments. The estimated information from both segments are almost identical, which demonstrates the identification is trustworthy. Besides, the stability diagrams from SSI-data method are very clean, and the poles associated with structural modes can become stabilized at very low model order. The research in this paper is meaningful for the platforms serving in cold regions, where the ices could be widespread. Utilizing the response from natural ice loading for modal parameter identification would be efficient and cost-effective.

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.

scholarly journals Modal Parameter Identification of Structures Using Reconstructed Displacements and Stochastic Subspace Identification

2021 ◽  
Vol 11 (23) ◽  
pp. 11432
Author(s):  
Xiangying Guo ◽  
Changkun Li ◽  
Zhong Luo ◽  
Dongxing Cao
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Moving Average ◽  
Random Fluctuation ◽  
High Frequency Component ◽  
Modal Parameters ◽  
Subspace Identification ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Stochastic Subspace Identification

A method of modal parameter identification of structures using reconstructed displacements was proposed in the present research. The proposed method was developed based on the stochastic subspace identification (SSI) approach and used reconstructed displacements of measured accelerations as inputs. These reconstructed displacements suppressed the high-frequency component of measured acceleration data. Therefore, in comparison to the acceleration-based modal analysis, the operational modal analysis obtained more reliable and stable identification parameters from displacements regardless of the model order. However, due to the difficulty of displacement measurement, different types of noise interferences occurred when an acceleration sensor was used, causing a trend term drift error in the integral displacement. A moving average low-frequency attenuation frequency-domain integral was used to reconstruct displacements, and the moving time window was used in combination with the SSI method to identify the structural modal parameters. First, measured accelerations were used to estimate displacements. Due to the interference of noise and the influence of initial conditions, the integral displacement inevitably had a drift term. The moving average method was then used in combination with a filter to effectively eliminate the random fluctuation interference in measurement data and reduce the influence of random errors. Real displacement results of a structure were obtained through multiple smoothing, filtering, and integration. Finally, using reconstructed displacements as inputs, the improved SSI method was employed to identify the modal parameters of the structure.

Application of Modal Analysis to Cylinder Structure Based on Random Vibration Test

2006 ◽  
Vol 5-6 ◽  
pp. 225-230
Author(s):  
C. Li ◽  
S. Hu ◽  
J. Li
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Random Vibration ◽  
Impulse Response Function ◽  
Vibration Test ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Exponential Method ◽  
Using Data ◽  
Complex Exponential

This paper presents the application of modal analysis and parameter identification using data of random vibration test to a cylinder structure. It is deduced that the impulse response function can be substituted by the cross-correlation function computed directly from the response-only data based on the white noise excitation or broadband input. So the modal parameter identification can be done by the least squares complex exponential (LSCE) method. And the modal parameters are obtained from the random vibration test data by the complex exponential method. Compared with the results of traditional modal test, the results of random vibration test are proved to be correct, and also the feasibility of this idea is proved well.

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