Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (6): 1580-1591.doi: 10.13229/j.cnki.jdxbgxb.20230077

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Spectrum⁃driven methods for modal parameter identification of bridge under environmental excitation

Yun-long ZHANG1(),Jia-yuan ZHANG1,Xue-song QIAN1(),Pan ZHANG2,Run-chao YANG3   

  1. 1.School of Communication Science and Engineering,Jilin Jianzhu University,Changchun 130118,China
    2.Changchun Construction Project Safety Supervision Station,Changchun 130012,China
    3.Jilin Province Highway Administration,Changchun 130021,China
  • Received:2023-01-30 Online:2023-06-01 Published:2023-07-23
  • Contact: Xue-song QIAN E-mail:zhangyunlong@jlju.edu.cn;qianxuesong@jlju.edu.cn

Abstract:

Firstly, the models used in parameter identification were summarized. Then, two popular techniques for frequency-domain identification were discussed, namely the Peak Picking method and the Complex Mode Indication Function method. The Peak Picking method is performed by selecting the modal frequency from the peak value of the output spectrum measured. While the Complex Mode Indication Function method is performed by diagonalizing the spectrum matrix. In addition, when the Complex Mode Indication Function is applied to the power spectral density, it becomes the reputed Frequency-Domain Decomposition method. Finally, the poly-reference Least Squares Complex Frequency domain method was discussed. This method shows advantages of low memory requirement, short computing time and high degree of automation, lying promising application in the operational modal analysis of bridge.

Key words: bridge structure, modal parameter, parameter identification, environmental excitation, frequency-domain techniques

CLC Number: 

  • U441.4
1 Reynders E. System identification methods for (operational) modal: review and comparison[J]. Archives of Computational Methods in Engineering, 2012, 19(1): 51-124.
2 Tan G J, Li H, Wang W S, et al. A rapid evaluation method based on natural frequency for post-earthquake traffic capacity of small and medium span bridges[J]. Engineering Structures, 2023, 280: No.115681.
3 Ljung L. System Identification: Theory for the User[M]. Upper Saddle River:Prentice Hall, 1999.
4 Heylen W, Lammens S, Sas P. Modal Analysis Theory and Testing[M]. Leuven: Katholieke Universiteit Leuven, 1997.
5 Maia N M M, Silva J M M. Theoretical and Experimental Modal Analysis[M]. Taunton: Research Studies Press, 1997.
6 Ewins D J. Modal Testing[M]. Baldock: Research Studies Press, 2000.
7 Pintelon R, Schoukens J. System Identification[M]. New York: IEEE Press, 2001.
8 Prevosto M. Algorithmes identification des caractéristiques vibratoires de structures mécaniques complexes[D]. Rennes: Université de Rennes, 1982.
9 Bendat J S, Piersol A G. Engineering Applications of Correlation and Spectral Analysis[M]. New York: Wiley-Interscience, 1980.
10 Brincker R, Zhang L, Anderden P. Modal identification from ambient responses using frequency domain decomposition[C]∥Proceedings of 18th IMAC, San Antonio, USA, 2000: 625-630.
11 Shih C Y, Tsuei Y G, Allemang R J, et al. Complex mode indication function and its applications to spatial domain parameter estimation[J]. Mechanical Systems and Signal Processing, 1988, 2(4): 367-377.
12 刘宇飞, 辛克贵, 樊健生, 等. 环境激励下结构模态参数识别方法综述[J]. 工程力学,2014, 31(4): 46-53.
Liu Yu-fei, Xin Ke-gui, Fan Jian-sheng, et al. A review of structure modal identification methods through ambient excitation[J]. Engineering Mechanics, 2014, 31(4): 46-53.
13 沈方伟, 杜成斌. 环境激励下结构模态参数识别方法综述[J]. 电子测试, 2013, 5: 178-181.
Shen Fang-wei, Du Cheng-bin. An overview of modal identification from ambient responses[J]. Electronic Test, 2013, 5: 178-181.
14 Brincker R, Ventura C, Andersen P. Damping estimation by frequency domain decomposition[C]∥Proceedings of the 19th International Modal Analysis Conference (IMAC), San Antonio, USA, 2000: 698-703.
15 van der Auweraer H, Guillaume P, Verboven P, et al. Application of a fast-stabilizing frequency domain parameter estimation method[J]. Journal of Dynamic Systems, Measurement, and Control, 2001, 123(4): 651-658.
16 Guillaume P, Verboven P, Vanlanduit S. Frequency-domain maximum likelihood identification of modal parameters with confidence intervals[J/OL]. [2023-01-15].
17 Guillaume P, Hermans L, Vander A H. Maximum likelihood identification of modal parameters from operational data[C]∥Proceedings of the 17th International Modal Analysis Conference, Florida, 1999: 1887-1893.
18 Guillaume P, Verboven P, Vanlanduit S, et al. A poly-reference implementation of the least squares complex frequency domain-estimator[C]∥Proceedings of the 21st International Modal Analysis Conference, Florida, USA, 2003: 1-9.
19 Peeters B, Van der Auweraer H, Guillaume P, et al. The PolyMAX frequency-domain method: a new standard for modal parameter estimation[J]. Shock and Vibration, 2004, 11(3/4): 395-409.
20 Magalhães F, Cunhan Á. Explaining operational modal analysis with data from an arch bridge[J]. Mechanical Systems and Signal Processing, 2011, 25:1431-1450.
21 Peeters B, Roeck G D. Stochastic system Identification for operational modal analysis: a review[J]. Journal of Dynamic Systems, Measurement, and Control, 2001, 123: 659-667.
22 Juang J N. Applied System Identification[M]. New Jersey: Prentice Hall, 1994.
23 Peeters B. System identification and damage detection in civil engineering[D]. Leuven: Katholieke Universiteit Leuven, 2000.
24 Akaike H. Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes[J]. Annals of the Institute of Statistical Mathematics, 1974, 26: 363-387.
25 Söderström T, Stoica P. Instrumental Variable Methods for System Identification[M]. New York: Springer, 1983.
26 Cauberghe B. Applied frequency-domain system identification in the field of experimental and operational modal analysis[D]. Brussel: Vrije Universiteit, 2004.
27 Reynders E. System identification and modal analysis in structural mechanics[D]. Leuven: Katholieke Universiteit, 2009.
28 Caines P. Linear Stochastic Systems[M]. New York: Wiley, 1998.
29 Golub G H, van Loan C F. Matrix Computations[M]. Baltimore: The Johns Hopkins University Press, 1996.
30 Hasan A, Danial M, Ahmad Z, et al. Enhanced frequency domain decomposition algorithm: a review of a recent development for unbiased damping ratio estimates[J]. Journal of Vibroengineering, 2018, 20(5): 1919-1936
31 Le T P, Paultre P. Modal identification based on the time-frequency domain decomposition of unknown-input dynamic tests[J]. International Journal of Mechanical Sciences, 2013, 71: 41-50.
32 Clough R W, Penzien J. Dynamics of Structures[M]. New York: McGraw-Hill, 1993.
33 Schoukens J, Pintelon R. Identification of Linear Systems: a Practical Guideline to Accurate Modelling[M]. London: Pergamon Press, 1991.
34 Pintelon R, Guillaume P, Rolain Y, et al. Parametric identification of transfer functions in the frequency domain-a survey[J]. IEEE Transactions on Automatic Control, 1994, 39(11): 2245-2260.
35 Vanlanduit S, Guillaume P, Schoukens J. High spatial resolution modal parameter estimation using a parametric MLE-like algorithm[C]∥Proceedings of ISMA23, International Conferenceon Noise and Vibration Noise and Vibration Engineering, Leuven, Belgium, 1998: 401-408.
36 Pintelon R, Schoukens J. Box-Jenkins identification revisited—part I: theory[J]. Automatica, 2006, 42(1): 63-75.
37 Pintelon R, Rolain Y, Schoukens J. Box-jenkins identification revisited—part II: applications[J]. Automatica, 2006, 42(1): 77-84.
38 Peeters B, Auweraer H. Polymax: a revolution in operational modal analysis, proceedings of the IOMAC[C]∥International Operational Modal Analysis Conference, Copenhagen, Denmark, 2005: No. 16131728.
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