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An example of application of soft computing in experimental modal analysis

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Konferencja
Neural Networks and Soft Computing/International Symposium (30.06-02.07.2005 ; Cracow, Poland)
Języki publikacji
EN
Abstrakty
EN
The paper deals with application of AI tools in experimental modal analysis. The example of Stabilization Diagram processing, that is an intermediate stage of modal parameter estimation procedure, was selected. In order to automate decision-making carried out during Stabilization Diagram processing a set of tools employing: fuzzy reasoning and artificial neural nets was applied. The application of these tools enabled to ease and shorten execution time of Stabilization Diagram processing. Additionally, the result of processing has become operator-independent.
Rocznik
Strony
277--292
Opis fizyczny
Bibliogr. 19 poz., tab., wykr.
Twórcy
autor
autor
autor
  • Department of Robotics and Mechatronics AGH - University of Science and Technology, Kraków, Poland
Bibliografia
  • [1] B. Cauberghe. Applied Freąuency-domain System Identification in the Field of Experimental and Operational Modal Analysis, PhD thesis. Vrije Universiteit Brussel, 2004
  • [2] K.S. Chhipwadia, D.C. Zimmerman, G.H. James III. Evolving autonomous modal parameter estimation. Proc. of 17th IMAĆ, SEM USA, 819-825, 1999.
  • [3] I. Goethals, B. Vanluyten, B. De Moor. Reliable spurious modę rejection using self learning algorithms. Proc. of ISMA2004, K.U. Leuven, 991-1003, 2004
  • [4] W. Heylen, S. Lammens, P. Sas. Modal Analysis Theory and Testing. K.U. Leuven, Departement Werktuigkunde, Leuven, 1997
  • [5] G.J. Klir, B. Yuan. Fuzzy Sets and Fuzzy Logic. Prentice Hall. 1995.
  • [6] W. Lisowski. Selected problems of decision-making during modal parameter estimation. Proc. of Int. Conf. on Structural Dynamics Modelling, Madeira Island, Portugal, 501-508. 2002.
  • [7] W. Lisowski, P. Kurowski. Applicability of selected indicators and algorithms for decision-making in an autonomous modal parameter estimation procedure. Proceedings of the ISMA2002, K.U. Leuven, 1369-1378, 2002.
  • [8] W. Lisowski, T. Uhl, P. Kurowski, K. Mendrok, G. Góral, A. Klepka.Example of autonomous parameter estimation procedure and its application to results of modal testing of an airplane. Proceedings of the ISMA2004, K.U. Leuven, 1019-1031, 2004.
  • [9] R.L. Mayes, S.E. Klenke. Automation and other extensions of the SMAC modal parameter extraction package. Proc. of 18th IMAĆ, SEM USA, 799-785, 2000.
  • [10] R.L. Mayes, S.E. Klenke. Consolidation of modal parameters from several extraction sets. Proc. of 19th IMAC, SEM USA, 1023-1028, 2001.
  • [11] L. Meirovitch. Elements of Vibration Analysis. McGraw-Hill, 1975.
  • [12] H.G. Natke, C. Cempel. Model-Aided Diagnosis of Mechanical Systems. Springer, 1997.
  • [13] R.S. Pappa, S.E. Woodard, J.-N. Juang. A benchmark problem for development of autonomous structural modal identification. Proc. of 15th IMAC, SEM USA, 1071-1077, 1997.
  • [14] M. Scionti, J. Lanslot, I. Goethals, A. Vecchio, H. Van der Auweraer, B. Peeters, B. De Moor. Tools to improve detection of structural changes from in-flight flutter data. Proc. of the Eight International Conference on Recent Advances in Structural Dynamics (ISVR), Southampton, UK, 12p., 2003
  • [15] R. Tadeusiewicz. Neural Network (in Polish). AOW, Warszawa, 1983.
  • [16] H. Van der Auweraer. Requirements and opportunities for structural testing in view of hybrid and virtual modeling. Proc. of ISMA 2002, KU Leuven, 1687-1702, 2002.
  • [17] P. Verboven, E. Parloo, P. Guillaume, M. Van Overmeire. Autonomous modal parameter estimation based on a statistical frequency domain maximum likelihood approach. Proc. of 19th IMAC, SEM USA, 1511-1517, 2001.
  • [18] P. Verboven, B. Cauberghe, P. Guillaume, S. Vanlanduit, E. Parloo. Modal parameter estimation and monitoring for online flight flutter analysis. Mechanical Systems and Signal Processing, 18(3): 587-610, 2004.
  • [19] R. Yager, D. Filev. Generation of fuzzy rules by mountain clustering. Journal of Intelligent and, Fuzzy Systems, 2(3): 209-219, 1994.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPB2-0026-0020
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