Modelling and study of PM machines with inter-turn fault dynamic model–FEM model

Vaseghi, Babak; Takorabet, Noureddine; Nahid‐Mobarakeh, Babak; Meibody‐Tabar, Farid

doi:10.1016/j.epsr.2011.03.017

Cited by 46 publications

(24 citation statements)

References 19 publications

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“…Model-based techniques are carried out by developing simulation models in numerous ways such as neural network, fuzzy logic, finite element method, time-stepped, state space, winding function approach, hidden Markov model-based semi non-parametric approach, etc. [4][5][6][7][8][9]17,18]. An analytical signal angular fluctuation method was proposed in [19] to discern rotor faults from load oscillations in case of asynchronous motors.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of different monitoring parameters for synchronous machine fault diagnostics

2016

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Early detection and diagnosis of faults in synchronous machine (SM) are crucial since they drive critical applications. In this paper, the authors exploited the combined information from numerical simulation and experimental validation to evaluate the merits of certain fault indicators, for detecting machine faults. A specially designed SM was chosen for both simulation and measurement with the ability to physically introduce electro-mechanical failures. Shorted turn fault was made through accessible intermediate terminals of respective stator and rotor windings. Eccentricity faults of different intensity were created by suitable changeover of customized end-shield. Finite element method was used to develop healthy and faulty simulation models. The experimental setup facilitated measurement and subsequent calculation of key parameters such as stator branch currents, phase current, circulating current, rotor field current and shaft voltage. From the investigation of both simulation and experimental data, field current and shaft voltage were found to be two effective fault indicators from safety and reliability prospects. Both indicators have the ability to identify and discriminate between electro-mechanical and electrical faults. Further, it is demonstrated that with availability of physical dimensions and measured rotor parameters, a know-how can be created to detect failures, well before a catastrophic event occurs.

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Section: Introductionmentioning

confidence: 99%

Evaluation of different monitoring parameters for synchronous machine fault diagnostics

2016

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“…Modeling and determining parameters of the machine with inter-turn fault can be used FEM to give much more pricise information of the machine [19], [21]. Usually a synchronous electric motor with magnet permanent uses FEA method to get motor electromagnetic parameter by using Ansoft Maxwell Model which is mainly used to build and analyze the PMSM [14]. The application of FEA for the PMSM design became an obligation in the recent years, and is now relatively easy to use first because of the capability to take into account the non-linearity of the magnetic material being suitable for a detailed study of the machien in its healthy state and under fault conditions [10], [11], [12].…”

Section: Introductionmentioning

confidence: 99%

“…This type of fault is counted a frequent fault and one of the most important reason of making out of order [15], [17]. It is caused by mechanical, electrical, environmental stresses and partial discharge, which is accelerated for electrical machines supplied by inverters [14], [20]. Modeling and determining parameters of the machine with inter-turn fault can be used FEM to give much more pricise information of the machine [19], [21].…”

Section: Introductionmentioning

confidence: 99%

Analysis and co-simulation of permanent magnet sychronous motor with short-circuit fault by finite element method

Fitouri

Bensalem

Abdelkrim

2016

2016 13th International Multi-Conference on Systems, Signals &Amp; Devices (SSD)

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This paper attempts to present a finite element analysis (FEA) and equivalent circuit simulation for PWM inverter fed permanent synchronous motor (PMSM). Here, the simulation is made using both the Ansys Maxwell and Simplorer. The finite element of the PMSM model is calculated and then its performance is optimized. This model is created in Maxwell two-Dimensional (2D). Moreover, the power inverter and control circuit are established based on the Ansys-Simplorer. The global dynamic model of the PMSM is obtained by co-simulation using Maxwell and Simplorer. The proposed model is exploited to analyze the system with faults caused by electric component such as the short circuit fault in the stator. Here the study of the machine in the faulty case is made and its effects are studied by the illustration of the simulation results.

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“…Extension to other driver types does not impose additional technical difficulties. For fault types, we will use the ones contained in [7], [9], [10], [11], [12].…”

Section: Introductionmentioning

confidence: 99%

“…Due to their utility in safety-sensitive applications, one of the essential issues in PM machines is fault detection and isolation [6], [7], [8], [9], [10], [11], [12]. For example, if a steering-wheel motor fails, the driver will lose control of a vehicle; if an electrical pump fails in a nuclear power plant, it can potentially result in a catastrophe.…”

Section: Introductionmentioning

confidence: 99%

System identification of permanent magnet machines and its applications to inter-turn fault detection

Progovac

Wang

Yin

2013

2013 IEEE Transportation Electrification Conference and Expo (ITEC)

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Permanent magnet machines are of high power density, high efficiency, small weight, and high reliability, and hence have found extensive applications. This paper employs system identification methods for stator winding fault detection and isolation, under noisy measurement data. Algorithms, estimation accuracy, and convergence properties are established. Simulation studies demonstrate the algorithms and their detection capability and reliability. Simulation results are used to illustrate potential usage of the methods.

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Modelling and study of PM machines with inter-turn fault dynamic model–FEM model

Cited by 46 publications

References 19 publications

Evaluation of different monitoring parameters for synchronous machine fault diagnostics

Evaluation of different monitoring parameters for synchronous machine fault diagnostics

Analysis and co-simulation of permanent magnet sychronous motor with short-circuit fault by finite element method

System identification of permanent magnet machines and its applications to inter-turn fault detection

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