Fault Diagnosis of Bearing Based on Selective Ensemble of Multiple Fuzzy ARTMAP Neural Networks
Zeng Bing Xu, Hong Lin Wu, Tie Lin Shi · Applied Mechanics and Materials · 2013
A novel selective ensemble of multiple fuzzy ARTMAP (FAM) classifiers based on the correlation measure method and Bayesian belief method is proposed to apply to the fault diagnosis of rolling element bearings in this paper. The test results show that the selective ensemble of four optimal FAM classifiers can identify the different fault categories accurately and has a better classification performance compared to the single FAM and ensemble of all FAM classifiers.