کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5005219 | 1369015 | 2010 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detection of broken rotor bars in induction motors using nonlinear Kalman filters
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
This paper presents a model-based fault detection approach for induction motors. A new filtering technique using Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) is utilized as a state estimation tool for on-line detection of broken bars in induction motors based on rotor parameter value estimation from stator current and voltage processing. The hypothesis on which the detection is based is that the failure events are detected by jumps in the estimated parameter values of the model. Both UKF and EKF are used to estimate the value of rotor resistance. Upon breaking a bar the estimated rotor resistance is increased instantly, thus providing two values of resistance after and before bar breakage. In order to compare the estimation performance of the EKF and UKF, both observers are designed for the same motor model and run with the same covariance matrices under the same conditions. Computer simulations are carried out for a squirrel cage induction motor. The results show the superiority of UKF over EKF in nonlinear system (such as induction motors) as it provides better estimates for rotor fault detection.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISA Transactions - Volume 49, Issue 2, April 2010, Pages 189-195
Journal: ISA Transactions - Volume 49, Issue 2, April 2010, Pages 189-195
نویسندگان
Farzaneh Karami, Javad Poshtan, Majid Poshtan,