Maximum current point tracking for stator winding short circuits diagnosis in Switched Reluctance Motor

Miremadi, Amir Hossein; Torkaman, Hossein; Siadatan, Alireza

doi:10.1109/pedstc.2013.6506678

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Despite its robustness and high reliability, the VRM is subject to several faults that can affect the mechanical, electrical and control parts or possibly combined faults [7,8]. The VRM is exposed to various and varied faults such as: static and dynamic eccentricity [9], short-circuit fault between turns and shortcircuit between phases, bearing faults, etc.…”

Section: Introductionmentioning

confidence: 99%

A combined variable reluctance network-finite element VR machine modeling for stator inter-turn short-circuit diagnosis

Chehda¹,

Benouzza²,

Bendiabdellah³

et al. 2020

IJECE

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<span lang="EN-US">The work presented in this paper, proposes a comparison study between the network variable reluctance (NVR) model and the finite elements (FE) model intended for the diagnosis of stator inter-turn short-circuit (ITSC) of the variable reluctance machine (VRM). In the first place, the model of the VRM by the NRV is presented. To validate this model, the FE model of the VRM has been then studied. The detection of the ITSC is achieved by the use of the stator current spectral analysis technique. The simulation results obtained, illustrate well the interest and efficiency of the proposed model as well as of the merits of the stator current spectral analysis technique for the stator ITSC fault diagnosis of the VRM.</span>

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Section: Introductionmentioning

confidence: 99%

A combined variable reluctance network-finite element VR machine modeling for stator inter-turn short-circuit diagnosis

Chehda¹,

Benouzza²,

Bendiabdellah³

et al. 2020

IJECE

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show abstract

“…As in (Paramasivam and Arumugam, 2004) certain works had been done using fuzzy controller to stablize the SRM. The papers (Gameiro and Cardoso, 2010;2012;Schinnerl and Gerling, 2009;Terec et al, 2011;Miremadi et al, 2013), discusses about the various power converters and faults likely to occur and methods to detect the faults. To the best of the author's knowledge, clustering algorithms and SVM based classification techniques had not been used in SRM fault detection.…”

Section: Introductionmentioning

confidence: 99%

Fault Detection in Switched Reluctance Motor Drives Using Discrete Wavelet Transform and K-Means Clustering

Chandrika¹

2014

American Journal of Applied Sciences

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This study presents a novel method of detection of inter turn shorts based on k means clustering technique. In addition to inter turn short detection, the other faults like open, short, phase to phase faults and DC voltage faults are detected through wavelet transforms and k means clustering. Open and short faults are classified using artificial neural network. All other faults are classified using Support Vector Machines (SVM). Switched reluctance motors are very popular in these days, because of ease in manufacturing and operation. Though an electronic circuit can detect the faults like open and short, the classification cannot be done effectively with electronic circuitry. More over an intelligent method can easily identify the fault and classify and hence the root cause of the fault may be guessed and rectified using this method of classification. This is highly possible with the time localization property of the wavelet transforms. So instant of fault occurrence can be detected along with the type of fault. The information used to include this intelligence in the system are just current waveforms, flux waveforms and torque waveforms. Inter turn shorts are very critical for a long run operation of the motor. Moreover, the early detection minimizes the faulty operation time and ensures the plant stability and saves the life of motor too. Hence an integrated system to detect the major faults under a simulation model has been proposed in this study.

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A Novel Control-Independent Online Fault Diagnosis of Interturn Short Circuits in SRMs Using Signal Injection Technique

Alam

Payami

2023

IEEE Trans. Ind. Electron.

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Maximum current point tracking for stator winding short circuits diagnosis in Switched Reluctance Motor

Cited by 4 publications

References 19 publications

A combined variable reluctance network-finite element VR machine modeling for stator inter-turn short-circuit diagnosis

A combined variable reluctance network-finite element VR machine modeling for stator inter-turn short-circuit diagnosis

Fault Detection in Switched Reluctance Motor Drives Using Discrete Wavelet Transform and K-Means Clustering

A Novel Control-Independent Online Fault Diagnosis of Interturn Short Circuits in SRMs Using Signal Injection Technique

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