Fault Diagnosis for Induction Motor with Rotor Broken Bar Fault Based on Multiple-model Estimation

被引：0
|
作者：
Zhu, Hongyu [1 ]
Mao, Zehui [1 ]
Jiang, Bin [1 ]
Liu, Hengbo [1 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Nanjing 211106, Jiangsu, Peoples R China
来源：
PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年
基金：
中国国家自然科学基金;
关键词：
Fault diagnosis; Induction Motor; Multiple-model estimation; Fusion estimation; SYSTEMS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the fault diagnosis problem for induction motor is studied on the basis of multiple-model estimation approach. Considering the time-varying parameters of motor with the changes of motor operation. a multiple model is proposed for induction motor with rotor broken bar fault. The corresponding Kalman filters are used to estimate the state under the random noise for each model. Based on the estimations from multiple model filters, the fault diagnosis algorithm is designed. Finally, the feasibility and effectiveness of the proposed method are illustrated by simulation.
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页码：7459 / 7464
页数：6
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