Publication Type : Journal Article
Publisher : Expert Systems with Applications
Source : Expert Systems with Applications, Volume 37, Number 6, p.4040 - 4049 (2010)
Url : http://www.sciencedirect.com/science/article/pii/S0957417409008689
Keywords : C4.5 algorithm, Fault diagnosis, Monoblock centrifugal pump, Statistical features
Campus : Coimbatore
School : School of Engineering
Department : Mechanical Engineering
Year : 2010
Abstract : 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.
Cite this Research Publication : Dr. Sakthivel N.R., Sugumaran, V., and Babudevasenapati, S., “Vibration based Fault Diagnosis of Monoblock Centrifugal Pump using Decision Tree”, Expert Systems with Applications, vol. 37, pp. 4040 - 4049, 2010.