A Winch Fault Classification Algorithm Based on Cluster Kernel Semi-Supervised Support Vector Machine

Xian Xin Shi; Zhong Xiang Zhao; Chang Jian Zhu; Xiao Xiao Kong; Jun Fei Chai; Li Jing Li; Huan Zhao

doi:10.4028/www.scientific.net/AMM.220-223.452

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 220-223A Winch Fault Classification Algorithm Based on...

A Winch Fault Classification Algorithm Based on Cluster Kernel Semi-Supervised Support Vector Machine

Abstract:

A cluster kernel semi-supervised support vector machine (CKS3VM) based on spectral cluster algorithm is proposed and applied in winch fault classification in this paper. The spectral clustering method is used to re-represent original data samples in an eigenvector space so as to make the data samples in the same cluster gather together much better. Then, a cluster kernel function is constructed upon the eigenvector space. Finally, a cluster kernel S3VM is designed which can satisfy the cluster assumption of semi-supervised study. The experiments on winch fault classification show that the novel approach has high classification accuracy.

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Periodical:

Applied Mechanics and Materials (Volumes 220-223)

Pages:

452-458

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.220-223.452

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Online since:

November 2012

Authors:

Xian Xin Shi, Zhong Xiang Zhao, Chang Jian Zhu, Xiao Xiao Kong, Jun Fei Chai, Li Jing Li, Huan Zhao

Keywords:

Cluster Kernel Function, Fault Classification, Semi-Supervised Support Vector Machine, Spectral Cluster Algorithm

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