Fuzzy Rule Extraction Based on Classfication Tree for Rotor System Fault Diagnosis
Da-Wei Meng · Energy Conservation Technology · 2005
Shaft faults is one of the main problems which cause turbo-generator breaks.Fault diagnosis based on expert systems is implemented for shafts in some power plant.Automatic learning is the core issue in applications of expert system.In this paper,an induction algorithm for classification trees is introduced.The algorithm is able to construct a classification tree from training data and transform the tree to a set of rules,which are widely used in expert systems.Then generalization of the induced rule set is analyzed based on minimal description length.We introduce support and confidence as measures of rule strength and give a pruning method.The experimental results show both attribute reduction and pruning methods will improve the recognition performance.