DocumentCode :
2740730
Title :
Three-phase Induction Motor Operation Trend Prediction Using Support Vector Regression for Condition-based Maintenance
Author :
Li, Yanfeng ; Yu, Haibin
Author_Institution :
Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang
Volume :
2
fYear :
0
fDate :
0-0 0
Firstpage :
7878
Lastpage :
7881
Abstract :
Due to the broad employment and large amount of electricity consumption of induction motor, their efficient operation has been a focus for engineering research. The paper proposes a new integrated approach performing the motor condition prediction for the maintenance of low cost and high quality. Studies were done on nonlinear data analysis techniques, including particle filters for state estimates and support vector regression for condition prediction. Laboratory studies support the condition-based maintenance for motor systems
Keywords :
data analysis; induction motors; maintenance engineering; regression analysis; state estimation; support vector machines; condition prediction; condition-based maintenance; nonlinear data analysis; particle filters; state estimation; support vector regression; three-phase induction motor operation trend prediction; AC motors; Costs; Data analysis; Electrical equipment industry; Electrical products industry; Employment; Energy consumption; Induction motors; Maintenance; Power system reliability; kernel method; maintenance; motor systems; prediction; regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1713504
Filename :
1713504
Link To Document :
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