TY - GEN
T1 - Structural health assessment after an impact
AU - Martinez-Flores, Rene
AU - Haldar, Achintya
AU - Katkhuda, Hasan
PY - 2006
Y1 - 2006
N2 - An innovative technique to assess structural health just after subjected to impulsive loadings (blasts, explosions, etc.) underdevelopment at the University of Arizona was experimentally verified and is presented in this paper. The authors called it the Generalized Iterative Least Square Extended Kalman Filter with Unknown Input (GILS-EKF-UI) method. The system is represented by finite elements and a Kalman filter-based system identification (SI) technique is used to identify the system. Some of the major characteristics of the method are that it does not require information on input excitation and can identify a system with limited noise-contaminated response information measured at few node points. To implement the Kalman-filter based algorithm, the information on the input excitation and the initial state vector must be available. The authors proposed a two-stage approach. In the first stage, based on the limited measured response information available at the locations of the sensors, a substructure is identified. After the completion of the first stage, the input excitation information that caused the responses and the stiffness of all the elements in the substructure can be evaluated. Then, in stage 2, the Kalman-filter based algorithm is used to identify the whole structure. The experimental verification of the method is emphasized in this paper.
AB - An innovative technique to assess structural health just after subjected to impulsive loadings (blasts, explosions, etc.) underdevelopment at the University of Arizona was experimentally verified and is presented in this paper. The authors called it the Generalized Iterative Least Square Extended Kalman Filter with Unknown Input (GILS-EKF-UI) method. The system is represented by finite elements and a Kalman filter-based system identification (SI) technique is used to identify the system. Some of the major characteristics of the method are that it does not require information on input excitation and can identify a system with limited noise-contaminated response information measured at few node points. To implement the Kalman-filter based algorithm, the information on the input excitation and the initial state vector must be available. The authors proposed a two-stage approach. In the first stage, based on the limited measured response information available at the locations of the sensors, a substructure is identified. After the completion of the first stage, the input excitation information that caused the responses and the stiffness of all the elements in the substructure can be evaluated. Then, in stage 2, the Kalman-filter based algorithm is used to identify the whole structure. The experimental verification of the method is emphasized in this paper.
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U2 - 10.1115/IMECE2006-13718
DO - 10.1115/IMECE2006-13718
M3 - Conference contribution
AN - SCOPUS:84920633934
SN - 0791837904
SN - 9780791837900
T3 - American Society of Mechanical Engineers, Safety Engineering and Risk Analysis Division, SERA
BT - Proceedings of 2006 ASME International Mechanical Engineering Congress and Exposition, IMECE2006 - Safety Engineering and Risk Analysis
PB - American Society of Mechanical Engineers (ASME)
T2 - 2006 ASME International Mechanical Engineering Congress and Exposition, IMECE2006
Y2 - 5 November 2006 through 10 November 2006
ER -