NDLI: Supervised Laplacian Eigenmaps for Machinery Fault Classification

Content Provider	IEEE Xplore Digital Library
Author	Quansheng Jiang Minping Jia
Copyright Year	2009
Abstract	Manifold learning is one of the efficient nonlinear dimensionality reduction techniques, which can be used to fault feature extraction. But they are not taking the class information of the data into account. In this paper, a new supervised Laplacian Eigenmaps algorithm (S-LapEig) for classification is proposed first. Via utilizing class information to guide the procedure of nonlinear mapping, the S-LapEig enhances local within-class relations and help to classification. Based on the S-LapEig, a novel fault classification approach is proposed. The approach uses the S-LapEig to extract feature for class labels data, and utilizes RBF network to map the unlabeled data to the feature space, which easily implement pattern classification and fault diagnosis. The experiments on benchmark data and real fault dataset demonstrate that, the proposed approach excels compared to PCA and Laplacian Eigenmaps, and it is an accurate technique for classification.
Starting Page	116
Ending Page	120
File Size	313285
Page Count	5
File Format	PDF
ISBN	9780769535074
DOI	10.1109/CSIE.2009.765
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Manifolds Fault diagnosis Laplace equations Pattern classification Radial basis function networks Feature extraction Classification algorithms Data mining Machinery Principal component analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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