Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30576
Kalman Filter Design in Structural Identification with Unknown Excitation

Authors: B. Moaveni, Z. Masoumi


This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Keywords: Structural health monitoring, Kalman Filter, structural system identification, Least square estimation

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1124


J. N. Yang, S. Pan, and S. Lin, "Identification and tracking of structural parameters with unknown excitations," in American Control Conference, 2004. Proceedings of the 2004, 2004, pp. 4189-4194.
[2] G. Sirca and H. Adeli, "System identification in structural engineering," Scientia Iranica, vol. 19, pp. 1355-1364, 2012.
[3] J. L. Beck and P. C. Jennings, "Structural identification using linear models and earthquake records," Earthquake Engineering & Structural Dynamics, vol. 8, pp. 145-160, 1980.
[4] J. H. Suk, Investigation and Solution of Problems for Applying Identification Methods to Real Systems: ProQuest, 2009.
[5] D. Wang and A. Haldar, "Element-level system identification with unknown input," Journal of Engineering Mechanics, vol. 120, pp. 159-176, 1994.