Observer Kalman Filter Identification for Output-Only Systems Using Interactive Structural Modal Identification Toolsuite
Publication: Journal of Bridge Engineering
Volume 19, Issue 5
Abstract
Several modal identification techniques have been developed in the past few decades, and their use is rapidly expanding due to new focus on the instrumentation of major structures. This paper focuses on the expansion of the eigenvalue realization algorithm (ERA)–observer Kalman filter identification (OKID) to identify modal parameters of output-only systems (OO) by splitting the state-space model into deterministic and stochastic subsystems (ERA-OKID-OO). The performance is then compared with other output-only identification methods in terms of the level of accuracy and efficiency. A newly developed software package [Structural Modal Identification Toolsuite (SMIT)] is used to provide a uniform and convenient way of utilizing several system identification (SID) methods, including variations of ERA, auto-regressive with exogenous terms (ARX) models, system realization using information matrix (SRIM), and numerical algorithms for subspace state space system identification (N4SID). The main purpose of SMIT is to provide a convenient platform for an expanding list of SID methods to estimate the modal parameters based on measured data and produce reports and compare them. With a brief explanation of the theoretical background of implemented algorithms, the paper continues with the preprocessing procedure to define the geometric information, sensor data, and setup for the applied method. It then explains the postprocessing procedure to construct stabilization diagrams, obtain modal parameters from the overparameterized estimation, and visualize and save the results. The applications for a numerically simulated simply supported beam as well as sensor data from the Lehigh River Bridge (LRB) on Highway 33 and Golden Gate Bridge (GGB) are used to demonstrate the validity of SMIT and investigate the performance of ERA-OKID-OO.
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Acknowledgments
This research was partially supported by the National Science Foundation under grant CMMI-0926898 by the Sensors and Sensing Systems program, and by a grant from the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA).
References
Andersen, P. (1997). “Identification of civil engineering structures using vector ARMA models.” Ph.D. thesis, Dept. of Building Technology and Structural Engineering, Aalborg Univ., Aalborg, Denmark.
Beck, J. L., and Jennings, P. (1980). “Structural identification using linear models and earthquake records.” Earthquake Eng. Struct. Dyn., 8(2), 145–160.
Bodeux, J., and Golinval, J. (2003). “Modal identification and damage detection using the data-driven stochastic subspace and ARMAV methods.” Mech. Syst. Sig. Process., 17(1), 83–89.
Chang, M., and Pakzad, S. N. (2012). SMIT v1.0, 〈http://smit.atlss.lehigh.edu〉 (Jul. 31, 2012).
Chang, M., and Pakzad, S. N. (2013). “Modified natural excitation technique for stochastic modal identification.” J. Struct. Eng., 1753–1762.
Chen, C. W., Huang, J. K., Phan, M., and Juang, J. N. (1992). “Integrated system identification and modal state estimation for control of large flexible space structures.” J. Guid. Control Dyn., 15(1), 88–95.
Dorvash, S., Pakzad, S. N., Knorr, R. C., and Horwath, L. M. (2011). “Modal identification of steel truss bridge using wireless sensor network.” Proc., 8th Int. Workshop on Structural Health Monitoring, International Workshop on Structural Health Monitoring, Stanford, CA.
Ewins, D. J. (1984). Modal testing: Theory and practice, Research Studies, Hertfordshire, U.K.
Flynn, E. B., et al. (2010). “SHMTools: A new embeddable software package for SHM applications.” Proc., SPIE 7647, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, Society of Photo-optical Instrumentation Engineers, Bellingham, WA.
Heylen, W., Lammens, S., and Sas, P. (1995). Modal analysis theory and testing, Dept. of Mechanical Engineering, Katholieke Univ. Leuven, Leuven, Belgium.
Ibrahim, S. R. (1977). “Random decrement technique for modal identification of structures.” J. Spacecraft Rockets, 14(11), 696–700.
Imai, H., Yun, C. B., Maruyama, O., and Shinozuka, M. (1989). “Fundamentals of system identification in structural dynamics.” Probab. Eng. Mech., 4(4), 162–173.
James, G. H. I., Carne, T. G., and Lauffer, J. P. (1993). “The natural excitation technique (NExT) for modal parameter extraction from operating wind turbines.” SAND92-1666, UC-261, Sandia National Laboratories, Albuquerque, NM.
Juang, J. N. (1994). Applied system identification, Prentice Hall, Englewood Cliffs, NJ.
Juang, J. N. (1997). “System realization using information matrix.” J. Guid. Control Dyn., 20(3), 492–500.
Juang, J. N., and Pappa, R. S. (1985). “An eigensystem realization algorithm for modal parameter identification and model reduction.” J. Guid. Control Dyn., 8(5), 620–627.
Ljung, L. (2008). “Perspectives on system identification.” Proc., 17th IFAC World Congress, International Federation of Automatic Control, Laxenburg, Austria, 17(1), 7172–7184.
MathWorks. (2009). MATLAB 7 getting started guide, 〈http://www.mathworks.com/access/helpdesk/help/pdf_doc/matlab/getstart.pdf〉 (Dec. 10, 2010).
Naganuma, T., Deodatis, G., and Shinozuka, M. (1987). “ARMA model for two-dimensional processes.” J. Eng. Mech., 234–251.
Nagarajaiah, S., et al. (2008). “Current directions of structural health monitoring and control in USA.” Adv. Sci. Tech., 56, 277–286.
Nagarajaiah, S., and Xiaohong, S. (2000). “Response of base-isolated USC hospital building in Northridge earthquake.” J. Struct. Eng., 1177–1186.
Pakzad, S. N. (2010). “Development and deployment of large scale wireless sensor network on a long-span bridge.” Smart Struct. Syst., 6(5–6), 525–543.
Pakzad, S. N., and Fenves, G. L. (2009). “Statistical analysis of vibration modes of a suspension bridge using spatially dense wireless sensor network.” J. Struct. Eng., 863–872.
Pakzad, S. N., Fenves, G. L., Kim, S., and Culler, D. E. (2008). “Design and implementation of scalable wireless sensor network for structural monitoring.” J. Infrastruct. Syst., 89–101.
Pandit, S. M. (1991). Modal and spectrum analysis, Wiley, New York.
Pappa, R., Elliott, K., and Schenk, A. (1993). “Consistent-mode indicator for the eigensystem realization algorithm.” J. Guid. Control Dyn., 16(5), 852–858.
Peeters, B., and De Roeck, G. (1999). “Reference-based stochastic subspace identification for output-only modal analysis.” Mech. Syst. Signal Process., 13(6), 855–878.
Pi, Y. L., and Mickleborough, N. C. (1989). “Modal identification of vibrating structures using ARMA model.” J. Eng. Mech., 2232–2250.
Reynders, E., Schevenels, M., and De Roeck, G. (2011). “MACEC 3.2: A Matlab toolbox for experimental and operational modal analysis.” Rep. BWM-2011-01, Dept. of Civil Engineering, Katholieke Univ. Leuven, Leuven, Belgium.
Sim, S. H., and Spencer, B. F., Jr. (2009). “Decentralized strategies for monitoring structures using wireless smart sensor networks.” NSEL Rep. Series, No. 19, Univ. of Illinois at Urbana-Champaign, Champaign, IL.
Smyth, A. W., Pei, J., and Masri, S. F. (2003). “System identification of the Vincent Thomas suspension bridge using earthquake records.” Earthquake Eng. Struct. Dyn., 32(3), 339–367.
Van Overschee, P., and De Moor, B. (1994). “N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems.” Automatica, 30(1), 75–93.
Welch, P. D. (1967). “The use of fast Fourier transforms for the estimation of power spectra: A method based on time averaging over short modified periodograms.” IEEE Trans. Audio Electroacoust., 15(2), 70–73.
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Published In
Journal of Bridge Engineering
Volume 19 • Issue 5 • May 2014
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© 2014 American Society of Civil Engineers.
History
Received: Nov 13, 2012
Accepted: Jul 1, 2013
Published online: Jul 4, 2013
Published in print: May 1, 2014
Discussion open until: Jun 2, 2014
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