Volume 3, Issue 3 (October 2007)                   IJEEE 2007, 3(3): 72-82 | Back to browse issues page

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F. Bagheri, H. Khaloozadeh, K. Abbaszadeh. Stator Fault Detection in Induction Machines by Parameter Estimation Using Adaptive Kalman Filter. IJEEE 2007; 3 (3) :72-82
URL: http://ijeee.iust.ac.ir/article-1-29-en.html
Stator Fault Detection in Induction Machines by Parameter Estimation Using Adaptive Kalman Filter
F. Bagheri , H. Khaloozadeh , K. Abbaszadeh
Abstract:   (14102 Views)
This paper presents a parametric low differential order model, suitable for mathematically analysis for Induction Machines with faulty stator. An adaptive Kalman filter is proposed for recursively estimating the states and parameters of continuous–time model with discrete measurements for fault detection ends. Typical motor faults as interturn short circuit and increased winding resistance are taken into account. The models are validated against winding function induction motor modeling which is well known in machine modeling field. The validation shows very good agreement between proposed method simulations and winding function method, for short-turn stator fault detection.
Keywords: Adaptive Kalman Filter , Fault Detection , Induction Machine , Parameter Estimation , Stator Faults
Full-Text [PDF 284 kb]   (4282 Downloads)    
Type of Study: Research Paper |
Received: 2008/10/07 | Accepted: 2013/12/30
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.