Application of Variable Precision Rough Set and Neural Network to Fault Diagnosis
Yueling Zhao · Journal of Liaoning University of Technology · 2010
Considering that the standard rough set theory cannot effectively process the noise data,in addition,there were always noise data in fault diagnosis data,a new method of SOM network-variable precision rough set-RBF neural network for fault diagnosis was proposed.Firstly,the continuous attributes in diagnostic decision system were discretized with SOM network.Then,reducts were found based on attribute dependence of variable precision rough set theory,and the optimal diagnostic decision was determined.Finally,according to the optimal decision system,RBF neural network was designed for fault diagnosis.A practical example was given to show the method is feasible and available,with high rate of accurate fault diagnosis obtained.