Identification of Linear Structures Using Discrete‐Time Filters
Publication: Journal of Structural Engineering
Volume 117, Issue 10
Abstract
Most of the previous studies considered structural system identification in the continuous‐time domain. The discrete‐time approach to the problem is more natural since all the recordings are in the discrete‐time form. This study presents a discrete‐time method for system identification by using discrete‐time linear filters. The method itself is well known in electrical and systems engineering fields, and therefore is not new. The objective in the paper is to present the method by emphasising its relation to the more familiar continuous‐domain modal analysis approach that is widely used in structural engineering. In addition to the method, some practical but important problems are also discussed in the paper, such as the processing of data, the selection and validation of models in the identification, and the detection of soil‐structure interaction. As an example, a 12‐story building was identified by using recordings from the magnitude 6.4, San Fernando, California earthquake of February 9, 1971.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Akaike, H. (1981). “Modern development of statistical methods.” Trends and progress in system identification. P. Eykhoff, ed., Pergamon Press, Elmsford, N.Y.
2.
Åström, K. J., and Wittenmark, B. (1984). Computer controlled systems. Prentice‐Hall, Englewood Cliffs, N.J.
3.
Bartlet, M. S. (1946). “The theoretical specification and sampling properties of autocorrelated time series.” J. Royal Statistical Society, Ser. B, 8, 27–41.
4.
Beck, J. L. (1978). Determining models of structures from earthquake records. Report No. EERL 78‐01, Earthquake Engrg. Res. Lab., California Inst. of Tech., Pasadena, Calif.
5.
Franklin, G. F., and Powell, J. D. (1980). Digital control of dynamic systems, Addison‐Wesley Publishing Company, Menlo Park, Calif.
6.
Frazer, R. A., Duncan, W. J., and Collar, A. R. (1946). Elementary matrices, Macmillan Comp., New York, N.Y.
7.
Gersch, W., and Luo, S. (1972). Discrete time series synthesis of randomly excited structural system response, J. Acoustic Society of America, 51, 402–408.
8.
Hurty, W. C., and Rubinstein, M. F. (1964). Dynamics of structures. Prentice‐Hall, Inc., Englewood Cliffs, N.J.
9.
Kozin, F., and Natke, H. G. (1986). System identification techniques. Struct. Saf, 3(3‐4), 269–316.
10.
Ljung, L. (1987). System identification: Theory for the user. Prentice Hall, Englewood Cliffs, N.J.
11.
Ljung, L., and Söderström T. (1983). Theory and practice of recursive identification. MIT Press, Cambridge, Mass.
12.
Şafak, E. (1988). “Analysis of recordings in structural engineering: Adaptive filtering, prediction, and control.” Open‐File Report No. 88‐647, U.S. Geological Survey, Menlo Park, Calif.
13.
Şafak, E. (1989a). Optimal‐adaptive filters to estimate spectral shape, site amplification, and source scaling. Soil Dyn. Earthquake Eng. 8(2).
14.
Şafak, E. (1989b). “Modeling, identification, and control of dynamic structural systems. I: Theory, Part II‐ Applications, J. Engrg. Mech., ASCE, 115(11).
15.
San Fernando, California, earthquake of February 9, 1971. (1973). National Oceanic and Atmospheric Administration, U.S. Department of Commerce, Washington, D.C.
16.
Tretter, S. A. (1976). Introduction to discrete‐time signal processing. John Wiley and Sons, New York, N.Y.
Information & Authors
Information
Published In
Copyright
Copyright © 1991 ASCE.
History
Published online: Oct 1, 1991
Published in print: Oct 1991
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.