Mine Fan Fault Diagnosis Based on EMD and SVM

Jun Fa Leng; Shuang Xi Jing

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

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 63-64Mine Fan Fault Diagnosis Based on EMD and SVM

Mine Fan Fault Diagnosis Based on EMD and SVM

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 63-64)

Pages:

449-452

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.63-64.449

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Online since:

June 2011

Authors:

Jun Fa Leng, Shuang Xi Jing

Keywords:

Empirical Mode Decomposition (EMD), Fault Feature Extraction, Mine Fan, Support Vector Machine (SVM)

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