TECHNICAL PAPERS
Aug 1, 2000

Parameter Identification of Large Structural Systems in Time Domain

Publication: Journal of Structural Engineering
Volume 126, Issue 8

Abstract

Though many methods of system identification are currently available for parameter estimation of structural systems, the challenge lies in the numerical difficulty in convergence when the number of unknowns is large. In this study, the genetic algorithms (GA) approach is adopted, which has several advantages over classical system identification techniques. Nevertheless, if applied directly, this approach requires tremendous computational time when dealing with structural systems large in both unknowns and degrees of freedom. A method is proposed herein to alleviate this problem by conducting a GA search in modal domains of a much smaller dimension than the physical domain. The objective function is defined based on the estimated modal response in time domain and the corresponding modal response transformed from the measured response. With some modification, this method also works well even with incomplete response measurement. Numerical examples of structural systems of up to 50 degrees of freedom are presented. Effects of measurement noise are considered.

Get full access to this article

View all available purchase options and get full access to this article.

References

1.
Asselmeyer, T., Ebeling, W., and Rose, H. (1997). “Evolutionary strategies of optimization.” Physical Rev. E, 56(1), 1171–1180.
2.
Bäck, T., Fogel, D. B., and Michalewicz, Z. (1997). Handbook of evolutionary computation, Oxford University Press, New York.
3.
Bäck, T., and Schwefel, H. P. (1993). “An overview of evolutionary algorithms for parameter optimization.” Evolutionary Computation, 1(1), 1–23.
4.
Bathe, K.-J. (1996). Finite element procedures, Prentice-Hall, Englewood Cliffs, N.J.
5.
Caravani, P., Watson, M. L., and Thomson, W. T. (1977). “Recursive least-squares time domain identification of structural parameters.” J. Appl. Mech., 44, 135–140.
6.
Carmichael, D. G. (1979). “The state estimation problem in experimental structural mechanics.” Proc., 3rd Int. Conf. on Application of Statistics and Probability in Soil and Struct. Engrg., Sydney, Australia, 802–815.
7.
Chen, J. H., and Lee, A. C. (1997). “Identification of linearized dynamic characteristics of rolling element bearings.” J. Vibration and Acoustics, 119, 60–69.
8.
Clough, R. W., and Penzien, J. (1993). Dynamic of structure, 2nd Ed., McGraw-Hill, New York.
9.
Cobb, R. G., and Liebst, B. S. (1997). “Structural damage identification using assigned partial eigenstructure.” AIAA J., 35(1), 152–158.
10.
Doyle, J. F. (1994). “A genetic algorithm for determining the location of structural impacts.” Experimental Mech., 34, 37–44.
11.
Doyle, J. F. (1995). “Determining the size and location of transverse cracks in beams.” Experimental Mech., 35, 272–280.
12.
Dunn, S. A. (1997). “Modified genetic algorithm for the identification of aircraft structures.” J. Aircraft, 34(2), 251–253.
13.
Dunn, S. A. (1998). “The use of genetic algorithms and stochastic hill-climbing in dynamic finite element model identification.” Comp. and Struct., 66(4), 489–497.
14.
Fogel, D. B. (1995). Evolutionary computation—toward a new philosophy of machine intelligence, IEEE Press, New York.
15.
Gen, M., and Cheng, R. W. (1996). Genetic algorithms and engineering design, Wiley, New York.
16.
Ghanem, R., and Shinozuka, M. (1995). “Structural-system identification. I: Theory.”J. Engrg. Mech., ASCE, 121(2), 255–264.
17.
Goldberg, D. (1989). Genetic algorithms in search, optimization and machine learning, Addison-Wesley, Reading, Mass.
18.
Grefenstette, J. J., Davis, L., and Cerys, D. (1991). GENESIS and OOGA: two genetic algorithm systems, Jan. TSP, Melrose, Mass.
19.
Herrmann, T., and Pradlwarter, H. J. (1998). “Two-step identification approach for damped finite element models.”J. Engrg. Mech., ASCE, 124(6), 639–647.
20.
Holland, J. (1975). Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor, Mich.
21.
Hoshiya, M., and Maruyama, O. (1987). “Identification of non-linear structural systems.” Proc., ICAP 5, 182–189.
22.
Hoshiya, M., and Satio, E. (1984). “Structural identification by extended Kalman filter.”J. Engrg. Mech., ASCE, 110(12), 1757–1770.
23.
Koh, C. G., See, L. M., and Balendra, T. (1991). “Estimation of structural parameters in time domain: a substructure approach.” Earthquake Engrg. and Struct. Dynamics, 20, 787–801.
24.
Koh, C. G., See, L. M., and Balendra, T. (1995a). “Determination of story stiffness of three-dimensional frame buildings.” Engrg. Struct., 17(3), 179–186.
25.
Koh, C. G., See, L. M., and Balendra, T. (1995b). “Damage detection of buildings: numerical and experimental studies.”J. Struct. Engrg., ASCE, 121(8), 1155–1160.
26.
Oreta, A. W. C., and Tanabe, T. A. (1994). “Element identification of member properties of framed structures.”J. Struct. Engrg., ASCE, 120(7), 1961–1976.
27.
Quek, S. T., Wang, W. P., and Koh, C. G. (1999). “System identification on linear MDOF structures under ambient excitation.” Earthquake Engrg. and Struct. Dynamics, 28, 61–77.
28.
Sato, T., and Qi, K. (1998). “Adaptive H-infinity filter: its application to structural identification.”J. Engrg. Mech., ASCE, 124(11), 1233–1240.
29.
Shinozuka, M., and Ghanem, R. (1995). “Structural-system identification. II: Experimental verification.”J. Engrg. Mech., ASCE, 121(2), 265–273.
30.
Udwadia, F. E., and Proskurowski, W. (1998). “A memory-matrix-based identification methodology for structural and mechanical systems.” Earthquake Engrg. and Struct. Dynamics, 27(12), 1465–1481.
31.
Wang, D., and Haldar, A. (1994). “Element-level system identification with unknown input.”J. Engrg. Mech., ASCE, 120(1), 159–176.
32.
Yun, C. B., Kim, W. J., and Ang, A. H. S. (1988). “Damaged assessment of bridge structures by system identification.” Proc., Korea-Japan Joint Seminar on Emerging Technol. in Struct. Engrg. and Mech., 182–193.
33.
Yun, C. B., and Lee, H. J. (1997). “Substructural identification for damage estimation of structures.” Struct. Safety, Amsterdam, 19(1), 121–140.
34.
Yun, C. B., and Shinozuka, M. (1980). “Identification of nonlinear structural dynamic system.” J. Struct. Mech., 8(2), 187–203.
35.
Zhao, F., Zeng, X., and Louis, S. (1997). “Genetic algorithms for inverse problem solutions.” Comp. in Civ. Engrg., Proc., 4th Congress, ASCE, New York, 725–732.

Information & Authors

Information

Published In

Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 126Issue 8August 2000
Pages: 957 - 963

History

Received: Oct 27, 1999
Published online: Aug 1, 2000
Published in print: Aug 2000

Permissions

Request permissions for this article.

Authors

Affiliations

Member, ASCE
Assoc. Prof., Dept. of Civ. Engrg., National Univ. of Singapore, 10 Kent Ridge Crescent, Singapore 119260.
Grad. Student, Dept. of Civ. Engrg., National Univ. of Singapore, 10 Kent Ridge Crescent, Singapore 119260.
Assoc. Prof., Dept. of Civ. Engrg., National Univ. of Singapore, 10 Kent Ridge Crescent, Singapore 119260.

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.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share