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2012 | OriginalPaper | Chapter

10. Condition Monitoring Using Support Vector Machines and Extension Neural Networks Classifiers

Author : Tshilidzi Marwala

Published in: Condition Monitoring Using Computational Intelligence Methods

Publisher: Springer London

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Abstract

Feature extraction and condition classification are considered in this chapter. The Feature extraction approaches applied in this chapter are fractals, Kurtosis and Mel-frequency Cepstral Coefficients. The classification approaches applied in this chapter are Support Vector Machines (SVMs) and Extension Neural Networks (ENNs). The usefulness of these features were tested with SVMs and ENNs for the condition monitoring of bearings and were found to give good results.

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Title: Condition Monitoring Using Support Vector Machines and Extension Neural Networks Classifiers
Author: Tshilidzi Marwala
Publisher: Springer London
Book: Condition Monitoring Using Computational Intelligence Methods
Print ISBN: 978-1-4471-2379-8

Electronic ISBN: 978-1-4471-2380-4

Copyright Year: 2012
DOI: https://doi.org/10.1007/978-1-4471-2380-4_10

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