Publications
Detailed Information
A New Online Bayesian Approach for the Joint Estimation of State and Input Forces using Response-only Measurements
Cited 0 time in
Web of Science
Cited 0 time in Scopus
- Authors
- Issue Date
- 2019-05-26
- Citation
- 13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019
- Abstract
- In this paper, a recursive Bayesian-filtering technique is presented for the joint estimation of the state and input forces. By introducing new prior distributions for the input forces, the direct transmission of the input into the state is eliminated, which allows removing low-frequency error components from the predictions and estimations. Eliminating such errors is of practical significance to the emerging fatigue monitoring methodologies. Furthermore, this new technique does not require a priori knowledge of the input covariance matrix and provides a powerful method to update the noise covariance matrices in a real-time manner. The performance of this algorithm is demonstrated using one numerical example and compared it with the state-of-the-art algorithms. Contrary to the present methods which often produce unreliable and inaccurate estimations, the proposed method provides remarkably accurate estimations for both the state and input.
- Language
- English
Item View & Download Count
Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.