A study of fault diagnose system of rotating machine based on rough sets
Baojie Xu · 2006
In order to extract simple and effective decision rules for fault diagnosis from the available original fault data containing inconsistent and redundant information,the attributes and attribute value are reduced through the proposed decision table reduction algorithms.A knowledge acquisition model based on rough sets is proposed in detail.The decision table is built by analyzing typical faults of rotating machine.This method solves the bottleneck of knowledge acquisition.Diagnostic results show the validity of the approach.