Synchronous generator incipient fault prediction based on SVM

Author

Huang Cao ; Yuan Haiwen ; Tian Bo ; Wu Qicai ; Yuan Haibing ; Ling Mu

Author_Institution

Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China

fYear

2014

fDate

9-11 June 2014

Firstpage

2115

Lastpage

2118

Abstract

Aiming at the lack of technology for generator incipient condition monitoring and fault prediction, proposed SVM(Support Vector Machine) is introduced to generator incipient fault prediction. This paper takes the parametric faults of synchronous generator as an example, selects the output voltage as a monitoring signal, and combines with SVM regression prediction algorithms to achieve synchronous generators incipient fault prediction.

Keywords

fault diagnosis; power engineering computing; support vector machines; synchronous generators; SVM regression prediction algorithms; generator incipient condition monitoring; parametric faults; support vector machine; synchronous generator incipient fault prediction; Circuit faults; Inductance; Mathematical model; Support vector machines; Synchronous generators; Threshold voltage; SVM; Synchronous generator; fault prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4799-4316-6

Type

conf

DOI

10.1109/ICIEA.2014.6931520

Filename

6931520

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=128772