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Volume 41 Issue 5
May  2015
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Journal of Beijing University of Aeronautics and Astronautics  > 2015  >  41(5): 811-816.
ZHOU Sida, ZHOU Xiaochen, LIU Li, et al. Fuzzy-clustering-based all-factor automatous validation approach of modal parameters of structures[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(5): 811-816. doi: 10.13700/j.bh.1001-5965.2014.0344(in Chinese)
Citation: ZHOU Sida, ZHOU Xiaochen, LIU Li, et al. Fuzzy-clustering-based all-factor automatous validation approach of modal parameters of structures[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(5): 811-816. doi: 10.13700/j.bh.1001-5965.2014.0344(in Chinese)
shu

Fuzzy-clustering-based all-factor automatous validation approach of modal parameters of structures

doi: 10.13700/j.bh.1001-5965.2014.0344

  • Key Laboratory of Dynamics and Control of Flight Vehicle, Ministry of Education, School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China

  • Received Date: 11 Jun 2014
  • Rev Recd Date: 22 Jul 2014
  • Publish Date: 20 May 2015
    Abstract
  • To solve the problem of modal parameter validation, an automatous validation approach of modal parameters was realize by using the fuzzy clustering analysis, which reduced the dependence of users' subjective experience on modal parameter validation, and improve the efficiency of modal parameter validation at modal analysis work. First, the modal parameters are divided into the scalar type and the vector type. Second, the scalar modal parameters were clustered by the convention fuzzy clustering approach. Third, the modal shape were fuzzy clustered by using a new proposed modal assurance criterion based metric function to solve the high-dimensional difficulty of fuzzy clustering. Then, combining the clustering results both of the scalar and the vector modal parameters, the all-factor automatous validation of modal parameters was accomplished. Finally, the proposed approach was validated by experimental results and illustrate that the proposed approach can automatously, accurately and high-efficiently validate the modal parameters.

     

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    • References(15)
  • [1]
    姚竹亭,潘宏侠.装甲车辆齿轮主传动系统的建模与辨识[J].振动、测试与诊断,2005,25(3):33-36. Yao Z T,Pan H X.Study on modeling and identification of main transmission system in armored vehicle[J].Journal of Vibration,Measurement & Diagnosis,2005,25(3):33-36(in Chinese).
    [2]
    Heylen W,Lammens S,Sas P.Modal analysis theory and testing[M].Belgium,Leuven:Katholieke Universiteit Leuven,2007:B.4.9-B.4.10.
    [3]
    杨毅青,刘强,Munoa J.基于正交多项式和稳定图的密集模态参数辨识[J].振动、测试与诊断,2010,30(4):429-433. Yang Y Q,Liu Q,Munoa J.Modal parameter identification of closely-coupled modes based on orthogonal polynomial and stabilization diagram[J].Journal of Vibration,Measurement & Diagnosis,2010,30(4):429-433(in Chinese).
    [4]
    Lanslots J,Rodiers B,Peeters B.Automated pole-selection:proof-of-concept & validation[C]//Proceedings of the ISMA International Conference on Noise and Vibration Engineering.Belgium,Leuven:Katholieke Universiteit Leuven,2004:1005-1018.
    [5]
    孙国富.基于模糊聚类的模态参数自动识别[J].振动与冲击,2010,29(9):86-88. Sun G F.Automatic modal parameters identification based on fuzzy clustering[J].Journal of Vibration and Shock,2010,29(9): 86-88(in Chinese).
    [6]
    Reynders E,Houbrechts J,de Roeck G.Fully automated (operational) modal analysis[J].Mechanical Systems and Signal Processing,2012,29:228-250.
    [7]
    Jain A K,Murty M N,Flynn P J.Data clustering: a review[J].ACM Computing Surveys,1999,31(3):264-323.
    [8]
    Lu J,Yuan X,Yahagi T.A method of face recognition based on fuzzy clustering and parallel neural networks[J].Signal Processing,2006,86(8):2026-2039.
    [9]
    Cinque L,Foresti G,Lombardi L.A clustering fuzzy approach for image segmentation[J].Pattern Recognition,2004,37(9):1797-1807.
    [10]
    ski J M,Owczarek A J.A time-domain-constrained fuzzy clustering method and its application to signal analysis[J].Fuzzy Sets and Systems,2005,155(2):165-190.
    [11]
    Hoppner F,Klawonn F,Kruse R,et al.Fuzzy cluster analysis:methods for classification,data analysis and image recognition[M].Chichester,West Sussex:John Wiley & Sons Ltd,1999:37-42.
    [12]
    Winkler R,Klawonn F,Kruse R.Problems of fuzzy c-means clustering and similar algorithms with high dimensional data sets[M].Berlin:Springer,2012:79-87.
    [13]
    Allemang R J.The modal assurance criterion(MAC):twenty years of use and abuse[J].Sound and Vibration,2003,37(8):14-23.
    [14]
    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.
    [15]
    Avitabile P.Modal space:The stability diagram has poles that are not indicated by the mmif or cmif;are they really modes [J].Experimental Techniques,2007,31(5):17-18.
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