LAPSE:2023.23587
Published Article

LAPSE:2023.23587
Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter
March 27, 2023
Abstract
Since the permeant magnet synchronous generator (PMSG) has many applications in particular safety-critical applications, enhancing PMSG availability has become essential. An effective tool for enhancing PMSG availability and reliability is continuous monitoring and diagnosis of the machine. Therefore, designing a robust fault diagnosis (FD) and fault tolerant system (FTS) of PMSG is essential for such applications. This paper describes an FD method that monitors online stator winding partial inter-turn faults in PMSGs. The fault appears in the direct and quadrature (dq)-frame equations of the machine. The extended Kalman filter (EKF) and unscented Kalman filter (UKF) were used to detect the percentage and the place of the fault. The proposed techniques have been simulated for different fault scenarios using MatlabĀ®/SimulinkĀ®. The results of the EKF estimation responses simulation were validated with the practical implementation results of tests that were performed with a prototype PMSG used in the Arab Academy For Science and Technology (AAST) machine lab. The results showed impressive responses with different operating conditions when exposed to different fault states to prevent the development of complete failure.
Since the permeant magnet synchronous generator (PMSG) has many applications in particular safety-critical applications, enhancing PMSG availability has become essential. An effective tool for enhancing PMSG availability and reliability is continuous monitoring and diagnosis of the machine. Therefore, designing a robust fault diagnosis (FD) and fault tolerant system (FTS) of PMSG is essential for such applications. This paper describes an FD method that monitors online stator winding partial inter-turn faults in PMSGs. The fault appears in the direct and quadrature (dq)-frame equations of the machine. The extended Kalman filter (EKF) and unscented Kalman filter (UKF) were used to detect the percentage and the place of the fault. The proposed techniques have been simulated for different fault scenarios using MatlabĀ®/SimulinkĀ®. The results of the EKF estimation responses simulation were validated with the practical implementation results of tests that were performed with a prototype PMSG used in the Arab Academy For Science and Technology (AAST) machine lab. The results showed impressive responses with different operating conditions when exposed to different fault states to prevent the development of complete failure.
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Keywords
extended Kalman filter (EKF), fault diagnosis (FD), permanent magnet synchronous generator (PMSG), stator inter-turn short circuit
Subject
Suggested Citation
El Sayed W, Abd El Geliel M, Lotfy A. Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter. (2023). LAPSE:2023.23587
Author Affiliations
El Sayed W: Electrical and control Department, College of Engineering and Technology, Arab Academy For Science and Technology and Maritime Transport, Abou Keer Campus, P.O. Box 1029, Alexandria 21500, Egypt; Institute of Automatics, Electronics and Electrical Enginee [ORCID]
Abd El Geliel M: Electrical and control Department, College of Engineering and Technology, Arab Academy For Science and Technology and Maritime Transport, Abou Keer Campus, P.O. Box 1029, Alexandria 21500, Egypt
Lotfy A: Electrical and control Department, College of Engineering and Technology, Arab Academy For Science and Technology and Maritime Transport, Abou Keer Campus, P.O. Box 1029, Alexandria 21500, Egypt
Abd El Geliel M: Electrical and control Department, College of Engineering and Technology, Arab Academy For Science and Technology and Maritime Transport, Abou Keer Campus, P.O. Box 1029, Alexandria 21500, Egypt
Lotfy A: Electrical and control Department, College of Engineering and Technology, Arab Academy For Science and Technology and Maritime Transport, Abou Keer Campus, P.O. Box 1029, Alexandria 21500, Egypt
Journal Name
Energies
Volume
13
Issue
11
Article Number
E2972
Year
2020
Publication Date
2020-06-09
ISSN
1996-1073
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Original Submission
Other Meta
PII: en13112972, Publication Type: Journal Article
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LAPSE:2023.23587
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https://doi.org/10.3390/en13112972
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Mar 27, 2023
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