Title :
The Damage Detection Based on the Fuzzy Clustering and Support Vector Machine
Author :
Tan, Dongmei ; Qu, Weilian ; Tu, Jianwei
Author_Institution :
Hubei Key Lab. of Roadway Bridge & Struct. Eng., Wuhan Univ. of Technol., Wuhan, China
Abstract :
In this paper, a damage detection algorithm based on the fuzzy clustering and support vector machine is presented. First, the acceleration data are decomposed by the wavelet packet transform to extract the wavelet packet component energy, which is used as the damage index. Second, the damage extent of the spatial truss structure is classified by fuzzy clustering. Finally the damage extent is identified using the support vector machine. The numerical example shows that the method can be effectively used to identify the damage of spatial truss structure, and the effect of noise on the algorithm is also studied.
Keywords :
condition monitoring; pattern clustering; structural engineering computing; support vector machines; supports; wavelet transforms; acceleration data; damage detection algorithm; damage index; fuzzy clustering; spatial truss structure; support vector machine; wavelet packet component energy; wavelet packet transform; Classification algorithms; Kernel; Noise; Support vector machines; Wavelet analysis; Wavelet packets; fuzzy clustering; spatial truss structure; support vector machine; wavelet packet transform;
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-8333-4
DOI :
10.1109/ISDEA.2010.404