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Diagnosis of Stator Inter-Turn Short Circuits in DTC Induction Motor Drives

Cruz, S.M.A., Cardoso, A.J.M.·2004·IEEE Transactions on Industry Applications

Abstract

This paper addresses the subject of stator fault diagnosis in direct torque control (DTC) induction motor drives. The particularities of the behavior of a DTC drive, when in the presence of inter-turn short circuits, are exploited, thus allowing the proposal of two different approaches for the diagnosis of this type of fault. One of the proposed diagnostic techniques is the well known motor current spectrum analysis. It is demonstrated that in a DTC induction motor drive, with stator inter-turn short circuits, the action of the torque and flux controllers introduce a strong third harmonic in the motor supply currents, which can be used to detect this type of fault. The other diagnostic technique is based on the multiple reference frames theory, recently proposed by the authors for the diagnosis of stator faults in line-connected motors. Here, its use is exploited in the diagnosis of stator faults in DTC induction motor drives. Simulation and experimental results demonstrate the effectiveness of the two proposed techniques for the diagnosis of stator faults but emphasize the fact that the multiple reference frames technique is the preferred one when the residual asymmetries of the motor are not negligible.

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Metadata

Authors
Cruz, S. M. A., & Cardoso, A. J. M.
Venue
IEEE Transactions on Industry Applications
Published
2004-09
Volume
40
Issue
5
Pages
1349-1360
ISSN
0093-9994 (ISSN-L)
OpenAlex
W2101536483
Cited by
185
References
0
FWCI
14.99
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Diagnosis of Stator Inter-Turn Short Circuits in DTC Induction Motor Drives. https://app.cochat.ai/papers/10.1109/tia.2004.834012
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Cruz, S. M. A., & Cardoso, A. J. M. (2004). Diagnosis of Stator Inter-Turn Short Circuits in DTC Induction Motor Drives. IEEE Transactions on Industry Applications. https://doi.org/10.1109/tia.2004.834012

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.