Title :
Decision rules analysis for induction motor fault diagnosis based on rough set theory
Author :
Yueling, Zhao ; Yingli, Wang
Author_Institution :
Coll. of Inf. Sci. & Eng., Liaoning Univ. of Technol., Jinzhou
Abstract :
In order to extract simple and effective diagnostic rules from inconsistent diagnostic information, the method of fault diagnosis based on rough set theory is proposed. The efficiency of diagnostic rules is improved by pruning rules with certainty factor and introducing the coverage factor of decision rules to remove redundant information effectively. The availability of this method is proved by a fault diagnosis example of induction motor.
Keywords :
fault diagnosis; induction motors; rough set theory; decision rules analysis; diagnostic rule; fault diagnosis; induction motor; pruning rule; rough set theory; Data mining; Educational institutions; Fault diagnosis; Induction motors; Information analysis; Information science; Information systems; Petrochemicals; Set theory; Certainty Factor; Coverage Factor; Decision rules; Fault Diagnosis; Rough Set;
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
DOI :
10.1109/CHICC.2008.4605450
