Detection of static eccentricity and turn-to-turn short circuit faults in permanent magnet synchronous AC machines

Haddad, Reemon Z.; Strangas, Elias G.

doi:10.1109/demped.2015.7303702

Cited by 18 publications

(11 citation statements)

References 17 publications

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“…The authors of [11] show the method of generation of incremental inductance curve by injecting d-axis current with increasing levels at constant speed operation. The steady state equations for the PMSM in d-q-axis reference frame are given as…”

Section: Current Injection In D-axis With Constant Rotationmentioning

confidence: 99%

“…Substituting Equations (11) and (12) in Equation 10, the total MMF in the stator frame of reference is…”

Section: Fundamentalmentioning

confidence: 99%

“…Also, in [9] it is shown that under higher operating loads, detection is difficult, but this paper does not discuss the operating load required for maximum separation between healthy and faulty case. Incremental inductance method is proposed in [10,11] to detect static eccentricity under offline conditions based on the shift in the peak of the curve. The authors of [10] used d-axis current with ac injection to generate incremental inductance curve.…”

Section: Introductionmentioning

confidence: 99%

“…The authors of [10] used d-axis current with ac injection to generate incremental inductance curve. The authors of [11] used a different method to generate the incremental inductance by applying current at different levels to the positive d-axis while the machine is running at a constant speed. However, the authors of [11] do not discuss the impact of difference in the levels of current on the incremental inductance curve.…”

Section: Introductionmentioning

confidence: 99%

“…The authors of [11] used a different method to generate the incremental inductance by applying current at different levels to the positive d-axis while the machine is running at a constant speed. However, the authors of [11] do not discuss the impact of difference in the levels of current on the incremental inductance curve. In the literature, voltage sub-harmonics in the machine are used for single fault detection.…”

Section: Introductionmentioning

confidence: 99%

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Review of Detection Methods of Static Eccentricity for Interior Permanent Magnet Synchronous Machine

Aggarwal

Strangas

2019

Energies

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This paper compares the detection methods of static eccentricity in Interior Permanent Magnet Synchronous Machines (IPMSM). Four methods are discussed: The first method uses shift in the voltages in d–q plane to detect fault. The second method uses shift in peak of the incremental inductance curve for fault detection. The third method uses the combined information of harmonics present both in current and voltage to detect the fault. This makes the detection robust with respect to current controller bandwidth. Finally, the fourth method used for detection includes measuring vibrations using accelerometers. It is shown that all four methods detected static eccentricity. These methods are compared on the basis of utility of fault detection under online or offline conditions and under saturated conditions. For all four methods the machine was tested at healthy, 25% and 50% static eccentricity levels. Two-dimensional (2-D) Finite element analysis was used for simulating machine under healthy and faulty cases. The experiments were performed by controlling the machine using Labview Real-time.

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Section: Current Injection In D-axis With Constant Rotationmentioning

confidence: 99%

“…Substituting Equations (11) and (12) in Equation 10, the total MMF in the stator frame of reference is…”

Section: Fundamentalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Review of Detection Methods of Static Eccentricity for Interior Permanent Magnet Synchronous Machine

Aggarwal

Strangas

2019

Energies

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Different Faults Diagnosis and Classification on‐Line in Permanent Magnet Synchronous Machines Using Improved Exponential Discriminant Analysis

Xiao

Gao

Hou

et al. 2020

IEEJ Transactions Elec Engng

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Reliability is an important performance for permanent magnet synchronous machine (PMSM) exploited to industrial applications and electric‐energy vehicles. Both air‐eccentricity and inter‐turn short circuit (ITSC) could induce the machine running in unbalanced status. Once not restored timely, the fault will lead to the whole drive system and its application damage. To enhance the reliability for PMSM, an effective fault diagnosis and classification method is necessary in advance. For this purpose, an improved exponential discriminant analysis (IEDA) algorithm is proposed and optimized. Further, the distortion characteristics of phase current signals with air‐eccentricity and ITSC are extracted and trained by the IEDA, which are applied for diagnosing whether the motor healthy or faulty and distinguishing fault types. Besides, the IEDA can not only identify fault type accurately but also estimate the fault degree precisely. Finally, compared to other common learning methods, several simulations and practical tests accompanying with diverse operating status are implemented, and their results can prove the proposed method has more accuracy and robustness than other methods. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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Identification and localization of incipient intermittent inter-turn fault in the stator of a three phase permanent magnet synchronous motor

Obeid

Battiston

Boileau

et al. 2017

2017 IEEE 11th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED)

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Detection of static eccentricity and turn-to-turn short circuit faults in permanent magnet synchronous AC machines

Cited by 18 publications

References 17 publications

Review of Detection Methods of Static Eccentricity for Interior Permanent Magnet Synchronous Machine

Review of Detection Methods of Static Eccentricity for Interior Permanent Magnet Synchronous Machine

Different Faults Diagnosis and Classification on‐Line in Permanent Magnet Synchronous Machines Using Improved Exponential Discriminant Analysis

Identification and localization of incipient intermittent inter-turn fault in the stator of a three phase permanent magnet synchronous motor

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