Research on temperature trend forecasting of rolling electric machine based on SVM

Author

Yi, Jiangang ; Liu, Hai

Author_Institution

Coll. of Machinery & Autom., Wuhan Univ. of Sci. & Technol., Wuhan

fYear

2008

fDate

25-27 June 2008

Firstpage

6844

Lastpage

6846

Abstract

A temperature trend forecasting algorithm based on support vector machine (SVM) was proposed to study the temperature faults of rolling electric machine. With the analysis of the monitoring system of rolling electric machine, the multi-steps forecasting model was built and the SVM algorithm was verified by a numerical example and a realistic case. The results show this algorithm has accurate forecasting ability and can help to diagnose faults in advance.

Keywords

computerised monitoring; electric machines; fault diagnosis; forecasting theory; production engineering computing; production equipment; rolling; support vector machines; temperature; fault diagnosis; monitoring system; multisteps forecasting model; rolling electric machine; support vector machine; temperature trend forecasting; Automation; Circulatory system; Condition monitoring; Cooling; Electric machines; Electric motors; Rotors; Support vector machines; Technology forecasting; Temperature sensors; Rolling Electric Machine; SVM; Temperature Trend Forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-2113-8

Electronic_ISBN

978-1-4244-2114-5

Type

conf

DOI

10.1109/WCICA.2008.4593972

Filename

4593972