Rotor Crack Detection Based on Multi-Vibration Signal Fusion Collected from the Basement of Machinery Using SVM and Statistical Characteristics Methodology

Abstract:

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As the poor generability of special sensor support frame and the inconvenience of signal acquisition in the process of common fault diagnosis for cracked rotor, a new fault diagnosis method is presented in this paper. this method takes the basement of rotor test rig as the monitoring objects and makes feature fusion for time-domain statistics of multiple sensors using SVM (support vector machine). The result of experiment showed that the method using the multi-sensor signal fusion technology collected from the basement of machinery has the advantages of better diagnostic precision for rotor crack diagnosis, furthermore, it supplies a new way for rotor fault diagnosis.

Info:

Periodical:

Edited by:

Shengyi Li, Yingchun Liu, Rongbo Zhu, Hongguang Li, Wensi Ding

Pages:

1000-1004

DOI:

10.4028/www.scientific.net/AMM.34-35.1000

Citation:

X. J. Li et al., "Rotor Crack Detection Based on Multi-Vibration Signal Fusion Collected from the Basement of Machinery Using SVM and Statistical Characteristics Methodology", Applied Mechanics and Materials, Vols. 34-35, pp. 1000-1004, 2010

Online since:

October 2010

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Price:

$35.00

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