Identification of civil structural parameters using the extended Kalman filter

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, February 2010.

Bibliographic Details
Main Author: Foun, Kevin
Other Authors: Jerome J. Connor.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2010
Subjects:
Online Access:http://hdl.handle.net/1721.1/57987
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author Foun, Kevin
author2 Jerome J. Connor.
author_facet Jerome J. Connor.
Foun, Kevin
author_sort Foun, Kevin
collection MIT
description Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, February 2010.
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spelling mit-1721.1/579872019-04-11T05:19:16Z Identification of civil structural parameters using the extended Kalman filter Foun, Kevin Jerome J. Connor. Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering. Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering. Civil and Environmental Engineering. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, February 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 175-179). In the context of civil and industrial structures, structural control and damage detection have recently become an area of great interest. The safety of a structure is always the most important issue for structural engineers, and to achieve this goal, the discipline of Structural Health Monitoring (SHM) was introduced. SHM records real-time information concerning structural conditions and performances. In order to evaluate the health conditions of structures, identifying the structural parameters is needed. Research activities of this area are increasing due to the availability of computation and wireless technologies. The objective of this thesis is to evaluate the tracking ability of the Kalman filter for identifying civil structural parameters based on measured vibration data which usually are earthquake accelerations. For linear elastic structures, the ordinary Kalman filter was used, but for nonlinear elastic structures, we implemented the extended Kalman filter. (cont.) For simulating damage occurrence in structures, a sudden change of stiffness was introduced, and an adaptive extended Kalman filter was utilized to estimate the time-varying parameters. In this thesis, linear and nonlinear structures with single-degree-of-freedom and multi-degree-of-freedom were simulated. Measurements having different levels of white noise were considered in order to evaluate the effects of noise on parametric estimations. In addition, the impacts of different levels of noise covariance were also discussed. Simulation results from different structural models were presented to demonstrate the effectiveness of the Kalman filter. by Kevin Foun. S.M. 2010-09-01T13:41:35Z 2010-09-01T13:41:35Z 2009 2010 Thesis http://hdl.handle.net/1721.1/57987 639574336 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 179 p. application/pdf Massachusetts Institute of Technology
spellingShingle Civil and Environmental Engineering.
Foun, Kevin
Identification of civil structural parameters using the extended Kalman filter
title Identification of civil structural parameters using the extended Kalman filter
title_full Identification of civil structural parameters using the extended Kalman filter
title_fullStr Identification of civil structural parameters using the extended Kalman filter
title_full_unstemmed Identification of civil structural parameters using the extended Kalman filter
title_short Identification of civil structural parameters using the extended Kalman filter
title_sort identification of civil structural parameters using the extended kalman filter
topic Civil and Environmental Engineering.
url http://hdl.handle.net/1721.1/57987
work_keys_str_mv AT founkevin identificationofcivilstructuralparametersusingtheextendedkalmanfilter