Abstract
When the modal parameters are changed quickly with time, they need to be identified at many moments to obtain the changing trend. To complete all the analysis manually is a very tremendous work, so the autonomous analysis is obligatory. Besides, for the test in which parameters are always changed with time, the data for computing FRF is short and excitation force is continuous. All these things make it difficult to obtain the precise FRFs which are necessary for autonomous modal analysis. To obtain the precise FRFs, in the paper, a direct time domain devolution method is presented to calculate the Impulse Response Functions (IRFs) for the first time. In the devolution algorithm, time-consuming inversion of matrix with large size is necessary. To avoid the matrix inversion, an effective iterative algorithm is put forward which can speed the calculation greatly at the cost of little accuracy reduction. In order to complete the modal analysis automatically, first, the modal analysis is completed manually at initial time and this analysis result will be as a preliminary reference model, the modal analysis of other times are completed total automatically. In the process, the previous analysis result is as the reference model, the stability diagram of current time is obtained by some methods such as ERA, PRCE, PolyMAX. Some poles are selected automatically by computing the pole weighted Modal Assurance Criterion (pwMAC) with the reference model. At the end of this paper, the real engineering example is introduced and the automatic analysis results are promising.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Juang J-N, Pappa RS (1985) An eigensystem realization algorithm for modal parameter identification and mode reduction. J Guid Control Dynam 8(1):620–627
Vold H, Rocklin GT (1982) The numerical implementation of a multi-input modal estimation method for mini-computers. In: Proceedings of the 1st IMAC, Orlando
Peeters B, Guillaume P, Van der Auweraer H et al (2004) Automotive and aerospace applications of the PolyMAX modal parameter estimation method. In: Proceedings of the 22th IMAC, Dearborn
Phillips AW, Allemang RJ (2005) Data presentation schemes for selection and identification of modal parameters. In: Proceedings of the 23th IMAC, Orlando, Florida
Ewins DJ (2001) Modal testing: theory, practice and application. Wiley, New York
Kay SM (1988) Modern spectral estimation theory and application. Prentice-Hall, Englewood Cliffs
Heylen W, Lammens S, Sas P (1998) Modal analysis theory and testing. Katholieke Universiteit Leuven, Belgium
Brigham EO (1974) The fast fourier transform. Prentice-Hall, Englewood Cliffs
Allemang R, Brown D, Rost R (1987) Experimental modal analysis and dynamic component synthesis. Measurement techniques for experimental analysis, Report AFWAL-TR-87-3069, vol II, OH, pp 29–40
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 The Society for Experimental Mechanics, Inc. 2012
About this paper
Cite this paper
Liu, J.M., Dong, S.W., Ying, M., Shen, S. (2012). Autonomous Identification of the Fast Time-Varied Modal Parameters. In: Allemang, R., De Clerck, J., Niezrecki, C., Blough, J. (eds) Topics in Modal Analysis I, Volume 5. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2425-3_11
Download citation
DOI: https://doi.org/10.1007/978-1-4614-2425-3_11
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-2424-6
Online ISBN: 978-1-4614-2425-3
eBook Packages: EngineeringEngineering (R0)