Identification method of excitation forces based on Kalman filter. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Liu, Xiao-Ang; Gao, Bo; Ma, Yechi; Jia, Xing; Xu, Bo; Xiao, Sen
• Is Part Of: Applied mathematics in science and engineering. Volume 30:Issue 1(2022)
• Page Start: 480
• Page End: 500
• Publication Date: 2022-01-02
• Subjects: Excitation force -- identification method -- Kalman filter -- minimum variance estimation; TB21; Science -- Mathematics -- Periodicals; Engineering mathematics -- Periodicals; Applied mathematics -- Periodicals; 501.51
• DOI: 10.1080/27690911.2022.2087648
• Languages: English
• ISSNs: 2769-0911

Abstract

Abstract : To identify the excitation forces of a vibration system, two identification methods are proposed, which take the displacement and acceleration responses of the system as input parameters. These two methods are based on the Kalman filter and minimum variance estimation method. The accumulation of identification errors in the iterative process is prevented through the non-iterative identification formula of the excitation force. The identification results and robustness of these two methods with different input parameters are analyzed. The results show that the identification accuracy of the method with acceleration as the input parameter is better than the method with displacement as the input parameter. Four types of hammer strike tests are performed. The test results show that the identification method with acceleration as the input parameter is effective in practical applications.