Title :
Application of FCM-HMM-SVM based mixed method for fault diagnosis of power electronic circuit
Author :
Cai, Jin-Ding ; Yan, Ren-Wu
Author_Institution :
Coll. of Electr. Eng. & Automatization, Fuzhou Univ., Fuzhou, China
Abstract :
Because of the problems of fault diagnosis in the power electric circuit and the merit of FCM is efficient in clustering and the merit of hidden Markov model (HMM ) that have the ability to deal with continuous dynamic signals and the merit of support vector machine (SVM ) with perfect classifying ability, FCM-HMM-SVM based diagnosing method is presented. With the features extracted from the circuit, based on the trained FCM algorithm, HMM was used to calculate the matching degree among the unknown signal and the circuit´s states, which formed the features for SVM to diagnosis. The experimental results show that the proposed method has a high correct rate.
Keywords :
fault diagnosis; fuzzy set theory; hidden Markov models; pattern clustering; power electronics; support vector machines; FCM-HMM-SVM based diagnosing method; fault diagnosis; fuzzy c-mean clustering; hidden Markov model; power electronic circuit; support vector machine; Circuit faults; Clustering algorithms; Educational institutions; Fault diagnosis; Hidden Markov models; Power electronics; Power system reliability; Support vector machine classification; Support vector machines; Testing; Discrete hidden markov model; Fault diagnosis; Fuzzy C-mean clustering; Power electronic circuit; Support vector machine;
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
DOI :
10.1109/MACE.2010.5535907