Application of Variable Precision Rough Set and Integrated Neural Network to Bearing Fault Diagnosis

Xiao Ling Niu; Bo Liu; Ke Zhang Lin

doi:10.4028/www.scientific.net/AMM.373-375.1060

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 373-375Application of Variable Precision Rough Set and...

Application of Variable Precision Rough Set and Integrated Neural Network to Bearing Fault Diagnosis

Abstract:

The integration of variable precision rough set and neural network is introduced into the bearing fault diagnosis. VPRS-INN fault diagnosis method is proposed: First, utilize the information entropy method for discretization of continuous attributes, and then use attribute dependence degree of the variable precision rough set theory for heuristic reduction. based on the reduction, obtain the optimal decision support system. Finally according to the optimal design system, we design a integrated neural network for fault diagnosis. instances have proved the feasibility and high fault diagnosis rate of the method.

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Periodical:

Applied Mechanics and Materials (Volumes 373-375)

Pages:

1060-1063

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.373-375.1060

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Online since:

August 2013

Authors:

Xiao Ling Niu, Bo Liu, Ke Zhang Lin

Keywords:

Bearing, Fault Diagnosis, Integrated Neural Network, Variable Precision Rough Set

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