Title :
Fault diagnosis approach of protective switching device based on support vector machines
Author :
Ma, Shaohua ; Zhao, Xiaofang
Author_Institution :
Coll. of Electr. Eng., Shenyang Univ. of Technol., Shenyang
Abstract :
A fault diagnosis approach of protective switching device (PSD) is presented in this paper. The support vector machines (SVM) which is a new kind of fault diagnosis methods is used to classify the faults including short circuit, overload, ..., etc. By training and learning, the fault model is built, the faults are diagnosed quickly and exactly, and accordingly the protection feature of PSD is improved.
Keywords :
electric machine analysis computing; fault diagnosis; machine protection; support vector machines; fault diagnosis approach; fault model; protective switching device; short circuit fault; support vector machines; Circuit faults; Fault diagnosis; Hydrogen; Machine learning; Microcomputers; Protection; Support vector machine classification; Support vector machines; Switches; Switching circuits;
Conference_Titel :
Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3826-6
Electronic_ISBN :
978-7-5062-9221-4
