IM stator winding faults diagnosis using EKF

Saad, Waseem W.; El-Geliel, Mostafa Abd; Lotfy, Ahmed

doi:10.1109/accs-peit.2017.8302997

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…The technique is simple and uses few numbers of sensors. Saad et al [19] propose the use of an extended Kalman filter technique to estimate the percentage of short circuit turns in each phase. This study used in different charges and in the presence of noise.…”

Section: Introductionmentioning

confidence: 99%

The Fast Prognosis of Inter-Turn Faults in an Induction Motor

Bouaissi,

Rezig,

Touati

2023

MMEP

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This paper introduces a novel approach for detecting and prognosing stator inter-turn faults in induction motors, addressing an important aspect of motor health monitoring. The most commonly employed method for fault detection in this context is Motor Current Signature Analysis (MCSA). By leveraging this method, the paper focuses on the generation of periodic Magneto Motive Force (MMF) waves in the balanced current signal as a result of inter-turn faults. These MMF waves serve as crucial indicators for identifying the presence of such faults. To achieve early detection and prognostic capability for inter-turn faults, the paper proposes a numerical model that relies on analyzing the forward and backward currents. This model offers a promising approach to effectively detect and prognose these faults before they escalate into more severe issues. The obtained results from applying the proposed method demonstrate its efficiency in fault detection and prognostic accuracy for stator inter-turn faults. To validate the effectiveness of the proposed approach, an experimental setup is implemented. This setup provides a real-world context for evaluating the performance and reliability of the method in detecting and prognosing inter-turn faults. Through this validation process, the paper strengthens the credibility and applicability of the proposed technique in practical motor maintenance and fault management scenarios.

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Section: Introductionmentioning

confidence: 99%

The Fast Prognosis of Inter-Turn Faults in an Induction Motor

Bouaissi,

Rezig,

Touati

2023

MMEP

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Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter

2020

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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.

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Proposing a Dynamic Model of Induction Motors Including Eccentricity and Stator Windings’ Faults

Haghighi

Zarabadipour²

2021

JoC

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A dynamic model in the d-q frame is introduced for wider coverage of the faults of three-phase induction motor. In this frame, it is possible to implement and analyze more accurately due to the evaluation of stator currents instead of rotor. In the proposed model, eccentricity and stator winding faults have been investigated. The results could cover more than 70% of the faults of the three-phase induction motor.

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IM stator winding faults diagnosis using EKF

Cited by 3 publications

References 9 publications

The Fast Prognosis of Inter-Turn Faults in an Induction Motor

The Fast Prognosis of Inter-Turn Faults in an Induction Motor

Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter

Proposing a Dynamic Model of Induction Motors Including Eccentricity and Stator Windings’ Faults

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