Fast Bayesian Ambient Modal Identification Incorporating Multiple Setups
Publication: Journal of Engineering Mechanics
Volume 138, Issue 7
Abstract
In full-scale ambient vibration tests, many situations exist where it is required to obtain a detailed mode shape of a structure with a limited number of sensors. A common feasible strategy is to perform multiple setups with each one covering a different part of the structure while sharing some reference degrees of freedom (DOF) in common. Methods exist that assemble the mode shapes identified in individual setups to form a global one covering all measured DOF. This paper presents a fast Bayesian method for modal identification capable of incorporating the fast Fourier transform information in different setups consistent with probability logic. The method allows the global mode shape to be determined, taking into account the quality of data in different setups. A fast iterative algorithm is developed that allows practical implementation even for a large number of DOF. The method is illustrated with synthetic and field test data. Challenges of the mode shape assembly problem arising in field applications are investigated through a critical appraisal.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This paper was funded by the Hong Kong Research Grant Council through General Research Fund (Project No. CityU 110210; 9041550). The financial support is gratefully acknowledged. The writers also would like to thank the following persons who participated in the field test: Dr Ching-Tai Ng, lecturer at the University of Adelaide; Ms. Yan-Chun Ni, graduate student at the City University of Hong Kong (CityU);, and Dr Xiu-Kai Yuan, senior research associate at CityU.
References
Au, S. K. (2011a). “Assembling mode shapes by least squares.” Mech. Syst. Signal Process., 25(1), 163–179.
Au, S. K. (2011b). “Fast Bayesian FFT method for ambient modal identification with separated modes.” J. Eng. Mech.JENMDT, 137(3), 214–226.
Au, S. K. (2012a). “Fast Bayesian ambient modal identification in the frequency domain, part I: posterior most probable value.” Mech. Syst. Signal Process., 26(1), 60–75.
Au, S. K. (2012b). “Fast Bayesian ambient modal identification in the frequency domain, part II: posterior uncertainty.” Mech. Syst. Signal Process., 26(1), 76–90.
Au, S. K., Ni, Y. C., Zhang, F. L., and Lam, H. F. (2012a). “Full-scale dynamic testing and modal identification of a coupled floor slab system.” Eng. Struct., 37, 167–178.ENSTDF
Au, S. K., and Zhang, F. L. (2011). “On assessing the posterior mode shape uncertainty in ambient modal identification.” Prob. Eng. Mech.PEMEEX, 26(3), 427–434.
Au, S. K., and Zhang, F. L. (2012). “Ambient modal identification of a primary-secondary structure by fast Bayesian FFT method.” Mech. Syst. Signal Process., 28, 280–296.
Au, S. K., Zhang, F. L., and To, P. (2012b). “Field observations on modal properties of two tall buildings under strong wind.” J. Wind Eng. Ind. Aerodyn.JWEAD6, 101(x), 12–23.
Beck, J. L. (2010). “Bayesian system identification based on probability logic.” Struct. Contr. Health Monit., 17(7), 825–847.
Brownjohn, J. M. W. (2003). “Ambient vibration studies for system identification of tall buildings.” Earthquake Eng. Struct. Dyn.IJEEBG, 32(1), 71–95.
Brownjohn, J. M. W., Moyo, P., Omenzetter, P., and Chakraborty, S. (2005). “Lessons from monitoring the performance of highway bridge.” Struct. Contr. Health Monit., 12(3–4), 227–244.
Caicedo, J. (2011). “Practical Guidelines for the Natural Excitation Technique (NExT) and the Eigensystem Realization Algorithm (ERA) for modal identification using ambient vibration.” Exp. Tech.EXPTD2, 35(4), 52–58.
Chang, P. C., Flatau, A., and Liu, S. C. (2003). “Health monitoring of civil infrastructure.” Struct. Health Monit., 2(3), 257–267.
Gentile, C., and Saisi, A. (2007). “Ambient vibration testing of historic masonry towers for structural identification and damage assessment.” Constr. Build. Mater.CBUMEZ, 21(6), 1311–1321.
Hart, G. C. (1996). “Random damping in buildings.” J. Wind Eng. Ind. Aerodyn., 59(2–3), 233–246.JWEAD6
Ivanovic, S. S., Trifunac, M. D., Novikovac, E. I., Gladkovc, A. A., and Todorovska, M. I. (2000). “Ambient vibration tests of a seven-story reinforced concrete building in Van Nuys, California, damaged by the 1994 Northridge earthquake.” Soil Dyn. Earthquake Eng.IJDEDD, 19(6), 391–411.
James, G. H., Carne, T. G., and Lauffer, J. P. (1995). “The natural excitation technique (NExT) for modal parameter extraction from operating structures.” Int. J. Anal. Exp. Modal Anal., 10(4), 260–277.
Jaynes, E. T. (2003). Probability theory: The logic of science, Cambridge Univ. Press, UK.
Ko, J. M., and Ni, Y. Q. (2005). “Technology developments in structural health monitoring of large-scale bridges.” Eng. Struct.ENSTDF, 27(12), 1715–1725.
Papadimitriou, C., Beck, J. L., and Katafygiotis, L. S. (2001). “Updating robust reliability using structural test data.” Prob. Eng. Mech.PEMEEX, 16(2), 103–113.
Peeters, B., and De Roeck, G. (2001). “One-year monitoring of the Z24-Bridge: environmental effects versus damage events.” Earthquake Eng. Struct. Dyn.IJEEBG, 30(2), 149–171.
Reynders, E., Pintelon, R., and De Roeck, G. (2008). “Uncertainty bounds on modal parameters obtained from stochastic subspace identification.” Mech. Syst. Signal Process., 22(4), 948–969.
Satake, N., Suda, K. I., Arakawa, T., Sasaki, A., and Tamura, Y. (2003). “Damping evaluation using full-scale data of buildings in Japan.” J. Struct. Eng.JSENDH, 129(4), 470–477.
Sohn, H., Farrar, C. R., Hemez, F. M., Shunk, D. D., Stinemates, D. W., and Nadler, B. R. (2003). “A review of structural health monitoring literature: 1996–2001.” Report, LA-13976-MS, Los Alamos National Laboratory, Santa Fe, NM.
Tamura, Y., and Suganuma, S. Y. (1996). “Evaluation of amplitude-dependent damping and natural frequency of buildings during strong winds.” J. Wind Eng. Ind. Aerodyn., 59(2–3), 115–130.JWEAD6
Van der Auweraer, H., and Peeters, B. (2003). “International research projects on structural health monitoring: an overview.” Struct. Health Monit., 2(4), 341–358.
Yuen, K. V., and Katafygiotis, L. S. (2003). “Bayesian fast Fourier transform approach for modal updating using ambient data.” Adv. Struct. Eng., 6(2), 81–95.
Zhang, F. L., and Au, S. K. (2011). “Ambient modal identification of a fan-shaped slab using Fast Bayesian FFT method.” 8th Int. Conf. on Structure Dynamics (EURODYN 2011), Leuven, Belgium, July 4–6.
Information & Authors
Information
Published In
Journal of Engineering Mechanics
Volume 138 • Issue 7 • July 2012
Pages: 800 - 815
Copyright
© 2012. American Society of Civil Engineers.
History
Received: Feb 24, 2011
Accepted: Dec 13, 2011
Published online: Jun 15, 2012
Published in print: Jul 1, 2012
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.