Online Model-Based Condition Monitoring for Brushless Wound-Field Synchronous Generator to Detect and Diagnose Stator Windings Turn-to-Turn Shorts Using Extended Kalman Filter

2016 ◽  
Vol 63 (5) ◽  
pp. 3228-3241 ◽  
Author(s):  
Sivakumar Nadarajan ◽  
Sanjib Kumar Panda ◽  
Bicky Bhangu ◽  
Amit Kumar Gupta
Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2972 ◽  
Author(s):  
Waseem El Sayed ◽  
Mostafa Abd El Geliel ◽  
Ahmed Lotfy

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 Matlab®/Simulink®. 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.


2017 ◽  
Vol 50 (1) ◽  
pp. 14100-14105 ◽  
Author(s):  
Ximei Wang ◽  
Xingkang He ◽  
Yanlong Zhao ◽  
Zhiqiang Zuo

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