Structural Parameter Identification in Time Domain using Extended Kalman Filter Method with Weighted Global Iteration
- https://doi.org/10.2991/icmii-15.2015.50How to use a DOI?
- structural parameter identification; extended Kalman filter method; memory fading filter technique; weighted global iteration; white noise
A structural parameter identification method is proposed to identify the stiffness parameters and damping coefficient and to estimate the unmeasured responses in time domain. The unique feature of this technique is that it requires only the displacement responses at all or most of dynamic degree-of- freedoms (DDOFs). This new method is a combination of the extended Kalman filter technique with weighted global iteration (EKF-WGI) technique, memory fading filter (MFF) technique and Runge-Kutta (R-K) method, and it is called as MFEKF-WGI by the authors. The parameter identification and the response estimation are carried out using the proposed method by a numerical example. Three noise contaminated cases of the displacement responses are considered. The robustness, efficiency and accuracy of the new technique are verified by the results. However, the proposed method requires more sample points and smaller time interval for the accuracy of estimation, and requires a complete response time histories for the estimation of unmeasured responses.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiang-Jian Wang AU - Jie Cui PY - 2015/10 DA - 2015/10 TI - Structural Parameter Identification in Time Domain using Extended Kalman Filter Method with Weighted Global Iteration BT - Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics PB - Atlantis Press SP - 267 EP - 276 SN - 2352-538X UR - https://doi.org/10.2991/icmii-15.2015.50 DO - https://doi.org/10.2991/icmii-15.2015.50 ID - Wang2015/10 ER -