TECHNICAL PAPERS
Feb 1, 2009

Adaptive Quadratic Sum-Squares Error for Structural Damage Identification

Publication: Journal of Engineering Mechanics
Volume 135, Issue 2

Abstract

The ability to detect damages online, based on vibration data measured from sensors, will ensure the reliability and safety of structures. Innovative data analysis techniques for the damage detection of structures have received considerable attention recently, although the problem is quite challenging. In this paper, we proposed a new data analysis method, referred to as the quadratic sum-squares error (QSSE) approach, for the online or almost online identification of structural parameters. Analytical recursive solution for the proposed QSSE method, which is not available in the previous literature, is derived and presented. Further, an adaptive tracking technique recently proposed is implemented in the proposed QSSE approach to identify the time-varying system parameters of the structure, referred to as the adaptive quadratic sum-squares error. The accuracy and effectiveness of the proposed approach are demonstrated using both linear and nonlinear structures. Simulation results using the finite-element models demonstrate that the proposed approach is capable of tracking the changes of structural parameters leading to the identification of structural damages.

Get full access to this article

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

Acknowledgments

This research is supported by the National Science Foundation Grant No. NSFCMS-0554814.

References

Alvin, K. F., Robertson, A. N., Reich, G. W., and Park, K. C. (2003). “Structural system identification: From reality to models.” Comput. Struct., 81, 1149–1176.
Bernal, D., and Beck, J. (2004). “Special section: Phase I of the IASC-ASCE structural health monitoring benchmark.” J. Eng. Mech., 130(1), 1–127.
Chang, F.-K., ed. (2005). Proc., 5th Int. Workshop on Structural Health Monitoring, Structural Health Monitoring, DEStech, Lancaster, Pa.
Ching, J., Beck, J. L., Porter, K. A., and Shaikhutdinov, R. (2006). “Bayesian state estimation method for nonlinear systems and its application to recorded seismic response.” J. Eng. Mech., 132(4), 396–410.
Doebling, S. W., Farar, C. R., and Prime, M. B. (1998). “A summary review of vibration-based damage identification methods.” Shock Vib. Dig., 30(2), 91–105.
Flores, R. M., and Haldar, A. (2005). “Experimental verification of a structural health assessment technique.” Proc., Structural Safety and Reliability, ICOSSAR 2005 (CD-ROM).
Goodwin, C. G., and Sin, K. S. (1984). Adaptive filtering: Prediction and control, Information and System Science Series, Prentice-Hall, Englewood Cliffs, N.J.
Hoshiya, M., and Saito, E. (1984). “Structural identification by extended Kalman filter.” J. Eng. Mech., 110(12), 1757–1771.
Lin, J. W., Betti, R., Smyth, A. W., and Longman, R. W. (2001). “On-line identification of nonlinear hysteretic structural systems using a variable trace approach.” Earthquake Eng. Struct. Dyn., 30, 1279–1303.
Ling, X., and Haldar, A. (2004). “Element level system identification with unknown input and Rayleigh damping.” J. Eng. Mech., 130(8), 877–885.
Loh, C. H., Lin, C. Y., and Huang, C. C. (2000). “Time domain identification of frames under earthquake loadings.” J. Eng. Mech., 126(7), 693–703.
Sato, T., and Chung, M. (2005). “Structural identification using adaptive Monte Carlo filter.” J. Struct. Eng., 51(A), 471–477.
Sato, T., Honda, R., and Sakanoue, T. (2001). “Application of adaptive Kalman filter to identify a five story frame structure using NCREE experimental data.” Proc., Structural Safety and Reliability, ICOSSAR 2001 (CD-ROM).
Sato, T., and Qi, K. (1998). “Adaptive H-infinity filter: Its application to structural identification.” J. Eng. Mech., 124(11), 1233–1240.
Smyth, A. W., Masri, S. F., Kosmatopoulos, E. B., Chassiakos, A. G., and Caughey, T. K. (2002). “Development of adaptive modeling techniques for non-linear hysteretic systems.” Int. J. Non-Linear Mech., 37(8), 1435–1451.
Tanaka, Y., and Sato, T. (2004). “Efficient system identification algorithm using Monte Carlo filter and its applications.” Proc. SPIE, 5394, 464–474.
Wen, Y. K. (1989). “Methods of random vibration for inelastic structures.” Appl. Mech. Rev., 42(2), 39–52.
Wu, M., and Smyth, A. W. (2007). “Application of the unscented Kalman filter for real-time nonlinear structural system identification.” Struct. Control Health Monit., 14(7), 971–990 (published online in Wiley InterScience).
Yang, J. N., and Huang, H. W. (2007a). “Sequential non-linear least square estimation for damage identification of structures with unknown inputs and unknown outputs.” Int. J. Non-Linear Mech., 42, 789–801.
Yang, J. N., Huang, H. W., and Lin, S. (2006a). “Sequential non-linear least-square estimation for damage identification of structures.” Int. J. Non-Linear Mech., 41, 124–140.
Yang, J. N., and Lin, S. (2004). “On-line identification of nonlinear hysteretic structures using an adaptive tracking technique.” Int. J. Non-Linear Mech., 39, 1481–1491.
Yang, J. N., and Lin, S. (2005). “Identification of parametric variations of structures based on least square estimation and adaptive tracking technique.” J. Eng. Mech., 131(3), 290–298.
Yang, J. N., Lin, S., Huang, H. W., and Zhou, L. (2006b). “An adaptive extended Kalman filter for structural damage identification.” Struct. Control Health Monit., 13, 849–867.
Yang, J. N., Pan, S., and Huang, H. W. (2006c). “Adaptive quadratic sum square error for damage identification of structures.” Proc., 4th China-Japan-U.S. Symp. on Structural Control and Monitoring, 100–106.
Yang, J. N., Pan, S., and Huang, H. W. (2007b). “An adaptive extended Kalman filter for structural damage identification. II: Unknown inputs.” Struct. Control Health Monit., 14(3), 497–521.
Yang, J. N., Pan, S., and Lin, S. (2007c). “Least square estimation with unknown excitations for damage identification of structures.” J. Eng. Mech., 133(1), 12–21.
Yoshida, I., and Sato, T. (2002). “Healthy monitoring algorithm by the Monte Carlo filter based on non-Gaussian noise.” J. Nat. Disaster Sci., 24(2), 101–107.
Yun, C. B., Lee, H. J., and Lee, C. G. (1997). “Sequential prediction error method for structural identification.” J. Eng. Mech., 123(2), 115–123.

Information & Authors

Information

Published In

Go to Journal of Engineering Mechanics
Journal of Engineering Mechanics
Volume 135Issue 2February 2009
Pages: 67 - 77

History

Received: Aug 24, 2006
Accepted: Aug 11, 2008
Published online: Feb 1, 2009
Published in print: Feb 2009

Permissions

Request permissions for this article.

Notes

Note. Associate Editor: Erik A. Johnson

Authors

Affiliations

Jann N. Yang, F.ASCE [email protected]
Professor, Dept. of Civil and Environmental Engineering, Univ. of California, Irvine, CA 92697. E-mail: [email protected]
Hongwei Huang [email protected]
Assistant Professor, Dept. of Bridge Engineering, Tongji Univ., Shanghai, China 200092. E-mail: [email protected]
Shuwen Pan
Graduate Student, Dept. of Civil and Environmental Engineering, Univ. of California, Irvine, CA 92697.

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