Underdetermined Blind Identification of Structures by Using the Modified Cross-Correlation Method
Publication: Journal of Engineering Mechanics
Volume 138, Issue 4
Abstract
The modified cross-correlation (MCC) blind identification method is extended to handle the underdetermined case of structural system identification. The underdetermined case is one in which the number of sensors is less than the number of identifiable modes. The basic framework of the modified cross-correlation method is retained in cases in which multiple covariance matrices constructed from the correlation of the responses are diagonalized. The solution to the underdetermined blind identification consists of two stages: the generation of intrinsic mode functions (IMFs) from the measurements by using empirical mode decomposition (EMD) and the application of the modified cross-correlation method to the decomposed signals. The available measurements are first decomposed into IMFs by using the sifting process of EMD. Subsequently, the IMFs are used as initial estimates for the sources, and the MCC method is implemented in an iterative framework. Initial estimates for the mixing matrix necessary to start the iterative process are selected using assumed shape functions that satisfy the essential boundary conditions. The need for sensor measurements at all the relevant degrees of freedom (DOF) to identify the mode shapes is alleviated in this approach. This is the main advantage of the proposed method. Vibration responses collected from the apron control tower located at the Toronto Pearson International Airport are used for demonstration.
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Acknowledgments
The authors gratefully acknowledge the financial support provided by the Natural Sciences and Engineering Research Council of Canada (NSERC) through their collaborative research and development (CRD) grants program. The authors also thank the Greater Toronto Airports Authority (GTAA) and Rowan Williams Davies and Irwin (RWDI), who served as the industrial partners in this project.
References
Antoni, J. (2005). “Blind separation of vibration components: Principles and demonstrations.” Mech. Syst. Signal Process., 19(6), 1166–1180.
Belouchrani, A., Abed-Meraim, K., Cardoso, J., and Moulines, E. (1997). “A blind source separation technique using second-order statistics.” IEEE Trans. Acoust., Speech, Signal Process., 45(2), 434–444.
Brincker, R., Zhang, L., and Anderson, P. (2001). “Modal identification of output-only systems using frequency domain decomposition.” Smart Mater. Struct., 10(3), 441–445.
Brownjohn, J. (2003). “Ambient vibration studies for system identification of tall buildings.” Earthquake Eng. Struct. Dyn., 32(1), 71–95.
Cichocki, A., and Amari, S. (2003). Adaptive blind signal and image processing, Wiley, New York.
Correa-Kijewski, T., and Pirnia, D. (2007). “Dynamic behaviour of tall buildings under wind: Insights from full-scale monitoring.” Struc. Design Tall Spec. Build., 16(4), 471–486.
Gul, M., and Catbas, F. N. (2008). “Ambient vibration data analysis for structural identification and global condition assessment.” J. Eng. Mech. Div., 134(8), 650–662.
Hazra, B., and Narasimhan, S. (2010). “Wavelet-based blind identification of the UCLA factor building using ambient and earthquake responses.” Smart Mater. Struct., 19(2), 025005.
Hazra, B., Roffel, A. J., Narasimhan, S., and Pandey, M. D. (2010a). “Modified cross-correlation method for the blind identification of structures.” J. Eng. Mech., 136(7), 889–897.
Hazra, B., Sadhu, A., Lourenco, R., and Narasimhan, S. (2010b). “Retuning tuned mass dampers using ambient vibration response.” Smart Mater. Struct., IOP Publishing, 19(11), 115002.
Huang, N. E., et al. (1998). “The empirical mode decomposition for the Hilbert spectrum for nonlinear and non-stationary time series analysis.” Proc. R. Soc. London, Ser. A, 454(1971), 903–995.
Hyvärinen, A., Karhunen, J., and Oja, E. (2001). Independent component analysis, Wiley, New York.
James, G., Carne, T., and Lauffer, J. (1995). “The natural excitation technique (NExT) for modal parameter extraction from operating structures.” Modal Anal., 10(4), 260–277.
Kerschen, G., Poncelet, F., and Golinval, J. (2007). “Physical interpretation of independent component analysis in structural dynamics.” Mech. Syst. Signal Process., 21(4), 1561–1575.
Kisilev, P., Zibulevsky, M., and Zeevi, Y. Y. (2003). “Multiscale framework for blind separation of linearly mixed signals.” J. Mach. Learn. Res., 1(1), 1–25.
Lus, H., Betti, R., and Longman, R. (1999). “Identification of linear structural systems using earthquake-induced vibration data.” Earthquake Eng. Struct. Dyn., 28(11), 1449–1467.
Maia, N. M. M. (1997). Theoretical and experimental modal analysis, Research Studies Press, Taunton, Somerset, UK.
Meirovitch, L. (1997). Principles and techniques of vibrations, Prentice Hall, Englewood Cliffs, NJ.
Nayeri, R., Masri, S., and Chassiakos, A. (2007). “Application of structural health monitoring techniques to track structural changes in a retrofitted building based on ambient vibration.” J. Eng. Mech., 133(12), 1311–1325.
Nayeri, R. D., Masri, S. F., Ghanem, R., and Nigbor, R. L. (2008). “A novel approach for the structural identification and monitoring of a full-scale 17-story building based on ambient vibration measurements.” Smart Mater. Struct., 17(2), 025006.
Peeters, B., and de Roeck, G. (2001). “Stochastic system identification for operational modal analysis: A review.” J. Dyn. Syst., Meas., Control, 123(4), 659–668.
Yang, J. N., Lei, Y., Lin, S., and Huang, N. (2004). “Identification of natural frequencies and dampings of in situ tall buildings using ambient wind vibration data.” J. Eng. Mech., 130(5), 570–577.
Yang, J. N., Lei, Y., Pan, S., and Huang, N. (2003). “System identification of linear structures based on Hilbert–Huang spectral analysis. Part 1: Normal modes.” Earthquake Eng. Struct. Dyn., 32(9), 1443–1467.
Yang, J. N., Pan, S., and Lin, S. (2007). “Least-squares estimation with unknown excitations for damage identification of structures.” J. Eng. Mech., 133(1), 12–21.
Zhou, W., and Chelidze, D. (2007). “Blind source separation based vibration mode identification.” Mech. Syst. Signal Process., 21(8), 3072–3087.
Zibulevsky, B., and Pearlmutter, B. (2001). “Blind source separation by sparse decomposition.” Neural Comput., 13(4), 863–882.
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© 2012 American Society of Civil Engineers.
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Received: Jan 6, 2010
Accepted: Aug 18, 2011
Published online: Aug 20, 2011
Published in print: Apr 1, 2012
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