Tikhonov regularization method for dynamic load identification

Peng-fei Cai; Pan Zhou; Tuo Shi; Jiang-lin Shao

doi:10.1117/12.2684938

19 October 2023 Tikhonov regularization method for dynamic load identification

Peng-fei Cai, Pan Zhou, Tuo Shi, Jiang-lin Shao

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 1270908 (2023) https://doi.org/10.1117/12.2684938
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

Dynamic load identification of simply supported rectangular plate was studied in this paper. As an inverse problem, ill-posed problem is prone to occur in identification process. In order to reduce ill-conditioned degree, Tikhonov regularization method was used for load identification, and regularization parameters were selected by ordinary cross validation, generalized cross validation and L curve method, respectively. The influence of response’s signal-to-noise-ratio on load identification accuracy is analyzed from a statistical point of view to provide some suggestions for engineering practice.

Citation Download Citation

Peng-fei Cai, Pan Zhou, Tuo Shi, and Jiang-lin Shao "Tikhonov regularization method for dynamic load identification", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 1270908 (19 October 2023); https://doi.org/10.1117/12.2684938

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available