Locating Impact on Structural Plate Using Principal Component Analysis and Support Vector Machines
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-16
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
A new method which integrates principal component analysis (PCA) and support vector machines (SVM) is presented to predict the location of impact on a clamped aluminum plate structure.
When the plate is knocked using an instrumented hammer, the induced time-varying strain signals are collected by four piezoelectric sensors which are mounted on the plate surface.
The PCA algorithm is adopted for the dimension reduction of the large original data sets.
Afterwards, a new two-layer SVM regression framework is proposed to improve the impact location accuracy.
For a comparison study, the conventional backpropagation neural networks (BPNN) approach is implemented as well.
Experimental results show that the proposed strategy achieves much better locating accuracy in comparison with the conventional approach.
American Psychological Association (APA)
Fu, Heming& Xu, Qingsong. 2013. Locating Impact on Structural Plate Using Principal Component Analysis and Support Vector Machines. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-1009094
Modern Language Association (MLA)
Fu, Heming& Xu, Qingsong. Locating Impact on Structural Plate Using Principal Component Analysis and Support Vector Machines. Mathematical Problems in Engineering No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-1009094
American Medical Association (AMA)
Fu, Heming& Xu, Qingsong. Locating Impact on Structural Plate Using Principal Component Analysis and Support Vector Machines. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-1009094
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009094