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Induction Motor Bearing Fault Detection based on ICA and ANN

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IJCA Proceedings on Emerging Applications of Electronics System, Signal Processing and Computing Technologies
© 2015 by IJCA Journal
NCESC 2015 - Number 1
Year of Publication: 2015
Authors:
Prashant D. Bharad
S. Subbaraman

Prashant D Bharad and S Subbaraman. Article: Induction Motor Bearing Fault Detection based on ICA and ANN. IJCA Proceedings on Emerging Applications of Electronics System, Signal Processing and Computing Technologies NCESC 2015(1):17-20, September 2015. Full text available. BibTeX

@article{key:article,
	author = {Prashant D. Bharad and and S. Subbaraman},
	title = {Article: Induction Motor Bearing Fault Detection based on ICA and ANN},
	journal = {IJCA Proceedings on Emerging Applications of Electronics System, Signal Processing and Computing Technologies},
	year = {2015},
	volume = {NCESC 2015},
	number = {1},
	pages = {17-20},
	month = {September},
	note = {Full text available}
}

Abstract

Independent component analysis (ICA) is one of the robust methods to extract the features. Many researchers have indicated a great potential for this approach to analyze the signals using ICA to detect the similarity or non-similarity between two signals. We have proposed a novel method which is extension of ICA to detect the faults associated with any machine by collecting vibration signals of machine. This paper presents the details of this method. The classification of the faults, if detected, is carried out using suitable classification technique.

References

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