Mine Fan Fault Diagnosis Based on EMD and SVM

Abstract:

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In this research, a new method based on EMD and SVM for mine fan fault diagnosis is introduced. With EMD, fault feature can be extracted quickly and accurately, and taken as the input samples for SVM with the outstanding non-linear pattern classification performances. 5 two-class SVM classifiers are designed in order to classify and diagnosis 5 typical fault patterns of mine fan. The result of this research shows that the integrative method of EMD and SVM is very fit for the intelligent diagnosis and fault patterns recognition, and it will lead to the possible development of an automated and on-line mine fan condition monitoring and diagnostic system.

Info:

Periodical:

Edited by:

Helen Zhang and David Jin

Pages:

449-452

DOI:

10.4028/www.scientific.net/AMM.63-64.449

Citation:

J. F. Leng and S. X. Jing, "Mine Fan Fault Diagnosis Based on EMD and SVM", Applied Mechanics and Materials, Vols. 63-64, pp. 449-452, 2011

Online since:

June 2011

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Price:

$35.00

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