Title :
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
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;
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
DOI :
10.1109/WCICA.2008.4593972
