Volume 8 Number 3 (Mar. 2013)
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JSW 2013 Vol.8(3): 709-715 ISSN: 1796-217X
doi: 10.4304/jsw.8.3.709-715

The Study on Rotating Machinery Early Fault Diagnosis based on Principal Component Analysis and Fuzzy C-means Algorithm

Qiang Zhao
Hebei University of Engineering, Handan, China, 056038

Abstract—This paper proposed an approach of mechanical failure information extraction and recognition in the early fault state variables, combined with the principal component analysis algorithm with FCM algorithm. Principal component analysis algorithm to get the characteristic value of data sets carries enough about fault in the time domain. Then FCM algorithm is used to analysis model is established in the classification feature different fault state. The application results of this method to identify variables deviation fault rotor test bed are acceptable.

Index Terms—Rotating machine; early fault diagnosis PCA; FCM.

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Cite: Qiang Zhao, "The Study on Rotating Machinery Early Fault Diagnosis based on Principal Component Analysis and Fuzzy C-means Algorithm," Journal of Software vol. 8, no. 3, pp. 709-715, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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