Fault prediction of power electronic circuits based on multi-scale relevance vector machine

Author

Zhang Yongliang ; Li Guolin ; Xie Xin

Author_Institution

Naval Aeronaut. & Astronaut. Univ., Yantai, China

fYear

2014

fDate

19-23 Oct. 2014

Firstpage

2292

Lastpage

2297

Abstract

Aiming at the issue that fault prediction of power electronic circuits is not accurate enough, a method based on multi-scale relevance vector machine (MSRVM) is proposed. Then the kernel parameters are optimized by Genetic Algorithm (GA) to avoid the negative affect on the performance of MSRVM by the non-ideal ones. The feasibility and advantages of MSRVM are proved by the fault prediction of a Buck converter circuit.

Keywords

electronic engineering computing; genetic algorithms; power electronics; support vector machines; GA; MSRVM; buck converter circuit; fault prediction; genetic algorithm; kernel parameters; multiscale relevance vector machine; power electronic circuits; Abstracts; Indexes; Integrated circuits; Kernel; Positron emission tomography; Prediction methods; Vectors; GA; MSRVM; fault prediction; kernel parameters optimization; power electronic circuits;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing (ICSP), 2014 12th International Conference on

Conference_Location

Hangzhou

ISSN

2164-5221

Print_ISBN

978-1-4799-2188-1

Type

conf

DOI

10.1109/ICOSP.2014.7015403

Filename

7015403

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=232241