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NC Machine Tools Fault Diagnosis Based on Kernel PCA and k -Nearest Neighbor Using Vibration Signals
Joint Authors
Yuqing, Zhou
Bingtao, Sun
Fengping, Li
Wenlei, Song
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-25
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This paper focuses on the fault diagnosis for NC machine tools and puts forward a fault diagnosis method based on kernel principal component analysis (KPCA) and k -nearest neighbor ( k NN).
A data-dependent KPCA based on covariance matrix of sample data is designed to overcome the subjectivity in parameter selection of kernel function and is used to transform original high-dimensional data into low-dimensional manifold feature space with the intrinsic dimensionality.
The k NN method is modified to adapt the fault diagnosis of tools that can determine thresholds of multifault classes and is applied to detect potential faults.
An experimental analysis in NC milling machine tools is developed; the testing result shows that the proposed method is outperforming compared to the other two methods in tool fault diagnosis.
American Psychological Association (APA)
Yuqing, Zhou& Bingtao, Sun& Fengping, Li& Wenlei, Song. 2015. NC Machine Tools Fault Diagnosis Based on Kernel PCA and k -Nearest Neighbor Using Vibration Signals. Shock and Vibration،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1077952
Modern Language Association (MLA)
Yuqing, Zhou…[et al.]. NC Machine Tools Fault Diagnosis Based on Kernel PCA and k -Nearest Neighbor Using Vibration Signals. Shock and Vibration No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1077952
American Medical Association (AMA)
Yuqing, Zhou& Bingtao, Sun& Fengping, Li& Wenlei, Song. NC Machine Tools Fault Diagnosis Based on Kernel PCA and k -Nearest Neighbor Using Vibration Signals. Shock and Vibration. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1077952
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1077952