Machine Learning Tools in Machinery Faults Diagnosis: A Review

Machine Learning Tools in Machinery Faults Diagnosis: A Review

Machinery faults can be detected by various signal processing tools; however, they require human expertise to achieve maximum success. Machine learning tools can help to achieve automatic machinery-faults diagnosis. This paper provides a brief review of the most common machine learning tools.

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Veröffentlicht in:Applied Mechanics and Materials 2014-06, Vol.575 (Materials Engineering and Automatic Control III), p.833-836
Hauptverfasser: Hee, Lim Meng, Hui, K.H., Leong, M. Salman
Format: Artikel
Sprache:eng
Schlagworte:
Automation
Diagnosis
Fault diagnosis
Faults
Human
Machine learning
Machinery
Signal processing
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Zusammenfassung:Machinery faults can be detected by various signal processing tools; however, they require human expertise to achieve maximum success. Machine learning tools can help to achieve automatic machinery-faults diagnosis. This paper provides a brief review of the most common machine learning tools.
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.575.833