Fault Diagnosis based on Rough Set and Dependent Feature Vector for Rolling Element Bearings
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The fault diagnosis of rolling element bearings (REB) has attracted substantial attention recently due to its importance for the bearing health management. The methods based on empirical mode decomposition and intelligent classification are widely used for REB fault diagnosis. However, there still exists two shortcomings in the fault diagnosis methods: 1) A large amount of redundant information is difficult to identify and delete; and 2) Aliasing patterns decreased the classification accuracy. To deal with these two shortcomings, an improved fault diagnosis method based on rough set and dependent feature vector (RS-DFV) is proposed in this paper. In RS-DFV method, the...