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Simultaneous identification of stiffness, mass, and damping using an on‐line model updating approach
Author(s) -
Huang XingHuai,
Dyke Shirley,
Sun Zhuoxiong,
Xu ZhaoDong
Publication year - 2017
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.1892
Subject(s) - stiffness , identification (biology) , kalman filter , truss , control theory (sociology) , line (geometry) , extended kalman filter , structural engineering , engineering , computer science , mathematics , artificial intelligence , botany , geometry , control (management) , biology
Summary The development of damage identification methods that enable rapid implementation holds great promise for assessing structural integrity to avoid further damage or catastrophic failure. Here, an on‐line model updating approach is proposed to rapidly and simultaneously identify the mass, stiffness, and damping properties of a structural model. The proposed approach facilitates identification of these unknown parameters using two steps: first, energy equilibrium equations are used to establish a relationship between structural energy and unknown parameters; second, the Kalman filter is adopted to obtain the unknown parameters in a short period of time. Numerical verification is conducted on a 158‐degree‐of‐freedom truss model with 324 unknown parameters based on a real‐world structure. The results indicate that the proposed approach can simultaneously identify the model parameters for the mass, stiffness, and damping of both the damaged and undamaged structures online, and also can effectively identify the stiffness damage and mass change, even in an environment with noise. Copyright © 2016 John Wiley & Sons, Ltd.