TY - JOUR
T1 - Fuzzy-clustering-based all-factor automatous validation approach of modal parameters of structures
AU - Zhou, Sida
AU - Zhou, Xiaochen
AU - Liu, Li
AU - Yang, Wu
N1 - Publisher Copyright:
©, 2015, Beijing University of Aeronautics and Astronautics (BUAA). All right reserved.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - To solve the problem of modal parameter validation, an automatous validation approach of modal parameters was realize by using the fuzzy clustering analysis, which reduced the dependence of users' subjective experience on modal parameter validation, and improve the efficiency of modal parameter validation at modal analysis work. First, the modal parameters are divided into the scalar type and the vector type. Second, the scalar modal parameters were clustered by the convention fuzzy clustering approach. Third, the modal shape were fuzzy clustered by using a new proposed modal assurance criterion based metric function to solve the high-dimensional difficulty of fuzzy clustering. Then, combining the clustering results both of the scalar and the vector modal parameters, the all-factor automatous validation of modal parameters was accomplished. Finally, the proposed approach was validated by experimental results and illustrate that the proposed approach can automatously, accurately and high-efficiently validate the modal parameters.
AB - To solve the problem of modal parameter validation, an automatous validation approach of modal parameters was realize by using the fuzzy clustering analysis, which reduced the dependence of users' subjective experience on modal parameter validation, and improve the efficiency of modal parameter validation at modal analysis work. First, the modal parameters are divided into the scalar type and the vector type. Second, the scalar modal parameters were clustered by the convention fuzzy clustering approach. Third, the modal shape were fuzzy clustered by using a new proposed modal assurance criterion based metric function to solve the high-dimensional difficulty of fuzzy clustering. Then, combining the clustering results both of the scalar and the vector modal parameters, the all-factor automatous validation of modal parameters was accomplished. Finally, the proposed approach was validated by experimental results and illustrate that the proposed approach can automatously, accurately and high-efficiently validate the modal parameters.
KW - All-factor
KW - Autonomous
KW - Clustering of mode shapes
KW - Fuzzy clustering
KW - Modal validation
UR - http://www.scopus.com/inward/record.url?scp=84930979822&partnerID=8YFLogxK
U2 - 10.13700/j.bh.1001-5965.2014.0344
DO - 10.13700/j.bh.1001-5965.2014.0344
M3 - Article
AN - SCOPUS:84930979822
SN - 1001-5965
VL - 41
SP - 811
EP - 816
JO - Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
JF - Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
IS - 5
ER -