TY - JOUR
T1 - Dynamic Load Identification for Structures with Unknown Parameters
AU - Tang, Hongzhi
AU - Jiang, Jinhui
AU - Mohamed, M. Shadi
AU - Zhang, Fang
AU - Wang, Xu
N1 - Funding Information:
Funding: This research is supported by the Foundation of National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics (No.61422202105), the Qing Lan Project and the National Natural Science Foundation of China (No.51775270).
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/11/18
Y1 - 2022/11/18
N2 - The inverse problem and the direct problem are symmetrical to each other. As a mathematical method for inverse problems, dynamic load identification is applicable to the situation when the load acting on the structure is difficult to measure directly. In addition, in most practical fields, the exact value of the structural parameters cannot be obtained precisely, which makes the inverse problem beyond the capabilities of traditional dynamic load identification methods. Hence, in this work, we propose a dynamic load identification algorithm based on the extended Kalman filter (EKF) for a structure with unknown parameters. The algorithm is discussed under different conditions where the unknown parameters are either the stiffness or the mass of the structure. Such a case has not been considered in other literature yet. In order to verify the advantages of the proposed method, the recursive least square method was also used to compare the results. A 5-Dof symmetric system with unknown coefficients was selected for numerical simulation examples, and the influence of noise on the algorithm was also considered in the simulation. The results show that the proposed algorithm is effective for structures with unknown mass and stiffness coefficients. Compared with the recursive least square method, the method proposed in this paper has the higher accuracy and a wider application scope.
AB - The inverse problem and the direct problem are symmetrical to each other. As a mathematical method for inverse problems, dynamic load identification is applicable to the situation when the load acting on the structure is difficult to measure directly. In addition, in most practical fields, the exact value of the structural parameters cannot be obtained precisely, which makes the inverse problem beyond the capabilities of traditional dynamic load identification methods. Hence, in this work, we propose a dynamic load identification algorithm based on the extended Kalman filter (EKF) for a structure with unknown parameters. The algorithm is discussed under different conditions where the unknown parameters are either the stiffness or the mass of the structure. Such a case has not been considered in other literature yet. In order to verify the advantages of the proposed method, the recursive least square method was also used to compare the results. A 5-Dof symmetric system with unknown coefficients was selected for numerical simulation examples, and the influence of noise on the algorithm was also considered in the simulation. The results show that the proposed algorithm is effective for structures with unknown mass and stiffness coefficients. Compared with the recursive least square method, the method proposed in this paper has the higher accuracy and a wider application scope.
KW - dynamic load identification
KW - extended Kalman filter
KW - recursive least square method
KW - unknown parameter
UR - http://www.scopus.com/inward/record.url?scp=85145269040&partnerID=8YFLogxK
U2 - 10.3390/sym14112449
DO - 10.3390/sym14112449
M3 - Article
VL - 14
JO - Symmetry
JF - Symmetry
SN - 2073-8994
IS - 11
M1 - 2449
ER -