Fuzzy logic based fault detection of PMSM stator winding short under load fluctuation using negative sequence analysis

Quiroga, Jabid; Liu, Li; Cartes, D.A.

doi:10.1109/acc.2008.4587163

Cited by 37 publications

(12 citation statements)

References 8 publications

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“…Since the voltages generated by the inverter are w.r.t the negative DC supply N and the neutral 'n' of the motor is floating, the zero sequence voltage needs to be accounted for in the model as shown in (8). The model for other healthy windings can be derived by setting the admittance function to Y h,expt (s) (9).…”

Section: Parametermentioning

confidence: 99%

“…Detection schemes are broadly divided into fundamental quantity based [6]- [8] detection, high frequency based [9], [10] detection and motor current signature analysis (MCSA) [11]. Most of the methods under MCSA are computationally intensive since they rely on performing fast Fourier transformation (FFT) to determine harmonic components and fault signature.…”

Section: Introductionmentioning

confidence: 99%

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Stator Inter-turn Fault Detection in SPM Machines Using PWM Ripple Current Measurement

Sen

Wang

2014

7th IET International Conference on Power Electronics, Machines and Drives (PEMD 2014)

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In this paper a novel method of inter-turn fault detection based on measurement of high frequency pulse width modulation (PWM) ripple current is proposed. The method uses the ripple current generated by the inverter itself as a means to detect inter-turn fault. High frequency impedance behaviours of healthy and faulted windings are analysed and modelled, and ripple current signature due to inter-turn faults is quantified. A simple analogue circuit is designed to extract the PWM ripple current via an RMS band-pass filter and the filtered RMS current is used for fault detection. In addition, the method also identifies the faulted phase. The method is tested in simulation on a five phase alternate slot wound SPM machine.

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Section: Parametermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stator Inter-turn Fault Detection in SPM Machines Using PWM Ripple Current Measurement

Sen

Wang

2014

7th IET International Conference on Power Electronics, Machines and Drives (PEMD 2014)

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“…In [21], K. H. Kim diagnoses the ITSC circuit fault by monitoring the harmonic currents for three-phase PMSM. J. Quiroga proposed a method for ITSC fault diagnosis of three-phase PMSM based on the fuzzy logic decoupling analysis of negative sequence current [22]. J. Urresty analyzed the zero-sequence voltage component (ZSVC) of the rotor three-phase voltage to diagnose the ITSC f i Fig.1 The schematic of five-phase PMSM with ITSC fault fault for three-phase PMSM [23].…”

Section: Introductionmentioning

confidence: 99%

Modeling and fault diagnosis of inter-turn short circuit for five-phase PMSM based on Particle Swarm Optimization

Yang

Dou

Dai

et al. 2016

2016 IEEE Applied Power Electronics Conference and Exposition (APEC)

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Multiphase PMSMs are widely used in faulttolerant control applications. And one of the important faulttolerant control problems is fault diagnosis. In most existing references, the fault diagnosis always focuses on three-phase PMSM. In this paper, a novel model and a fault diagnosis method of inter-turn short circuit (ITSC) fault for five-phase PMSM based on particle swarm optimization (PSO) are presented. There are two contributions in this paper: 1) By analyzing the physical parameters of the PMSM, such as resistance, inductance and flux, the mathematic model of ITSC fault for five-phase PMSM is established. 2) A parameter estimation method based on PSO algorithm, which introduces a fitness function related to the ITSC ratio and reformulates the fault parameters identification problem as the extreme seeking problem, is proposed to track the actual ITSC ratio and detect the fault level for five-phase PMSM. Simulation results provide preliminary verification of the proposed model and fault diagnosis method.

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“…The main widely used technique is based on the motor stator current analysis. In [5], a negative sequence analysis coupled with a fuzzy logic based approach has been used for fault diagnosis of a PMSM. In [6], a fault model has been proposed for inter-turn fault model, a series of algorithms have been proposed for fault detection and diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of inter-turn short-circuit stator winding fault in PMSM based on stator current and noise

Liang

2014

2014 IEEE International Conference on Industrial Technology (ICIT)

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In this paper, the method of stator current and noise combination is introduced for inter-turn short-circuit fault recognition in permanent magnet synchronouse motor. The detection and diagnosis system consists of sensors, USB5935 data acquisiton card USB5935 and a computer with LabVIEW installed. The frequency pattern of stator current is extracted from the monitored stator current and the amplitude of increase is obtained. The frequency pattern of noise is extracted from the monitored noise and the main fault frequency is found. The frequency pattern of stator current and the amplitude of increase are introduced as a main criterion to diagnose the inter-turn short-circuit fault. The frequency pattern of noise is introduced as a secondary criterion. The experiment shows that the combination of the stator current and noise is helpful to diagnose the small inter-turn short-circuit fault of permanent magnet synchronouse motor.

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Fuzzy logic based fault detection of PMSM stator winding short under load fluctuation using negative sequence analysis

Cited by 37 publications

References 8 publications

Stator Inter-turn Fault Detection in SPM Machines Using PWM Ripple Current Measurement

Stator Inter-turn Fault Detection in SPM Machines Using PWM Ripple Current Measurement

Modeling and fault diagnosis of inter-turn short circuit for five-phase PMSM based on Particle Swarm Optimization

Diagnosis of inter-turn short-circuit stator winding fault in PMSM based on stator current and noise

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