Vibration based fault diagnosis of monoblock centrifugal pump using decision tree

Monoblock centrifugal pumps are widely used in a variety of applications. In many applications the role of monoblock centrifugal pump is critical and condition monitoring is essential. Vibration based continuous monitoring and analysis using machine learning approaches are gaining momentum. Particul...

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Bibliographic Details
Published in:	Expert systems with applications Vol. 37; no. 6; pp. 4040 - 4049
Main Authors:	Sakthivel, N.R., Sugumaran, V., Babudevasenapati, S.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01-06-2010
Subjects:	Algorithms C4.5 algorithm Centrifugal pumps Decision trees Expert systems Fault diagnosis Fuzzy logic Monitoring Monoblock centrifugal pump Statistical features Vibration Monoblock centrifugal pump Fault diagnosis C4.5 algorithm Statistical features
Online Access:	Get full text
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Summary:	Monoblock centrifugal pumps are widely used in a variety of applications. In many applications the role of monoblock centrifugal pump is critical and condition monitoring is essential. Vibration based continuous monitoring and analysis using machine learning approaches are gaining momentum. Particularly artificial neural networks, fuzzy logic were employed for continuous monitoring and fault diagnosis. This paper presents the use of C4.5 decision tree algorithm for fault diagnosis through statistical feature extracted from vibration signals of good and faulty conditions.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0957-4174 1873-6793
DOI:	10.1016/j.eswa.2009.10.002