Inter-Turn Fault Detection in Stator Winding of PMSM Using Wavelet Transform

Moosavi, Seyed Saeid; Esmaili, Qadir; Djerdir, Abdesslem; Amirat, Youcef

doi:10.1109/vppc.2017.8330891

Cited by 22 publications

(10 citation statements)

References 7 publications

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“…N kn (9) where ω(n) is the window function, k represents the frequency index, N represents the number of FFT points; m represents the position of window, and H represents the jump distance between two consecutive windows.…”

Section: Short-time Fourier Transformmentioning

confidence: 99%

“…When is compared with STFT, the window size a and b of WT can vary with the frequency. Therefore, with WT, the signal can be decomposed into signals at different frequency bands with different resolutions, which makes it suitable for accurate and flexible fault detection of PMSM [9]. Rosero et al have evaluated the degree of demagnetization of PMSM by calculating the energy in the detail of DWT [61].…”

Section: Wavelet Transformmentioning

confidence: 99%

See 1 more Smart Citation

Faults and Diagnosis Methods of Permanent Magnet Synchronous Motors: A Review

et al. 2019

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Permanent magnet synchronous motors (PMSM) have been used in a lot of industrial fields. In this paper, a review of faults and diagnosis methods of PMSM is presented. Firstly, the electrical, mechanical and magnetic faults of the permanent magnet synchronous motor are introduced. Next, common fault diagnosis methods, such as model-based fault diagnosis, different signal processing methods, and data-driven diagnostic algorithms are enumerated. The research summarized in this paper mainly includes fault performance, harmonic characteristics, different time-frequency analysis techniques, intelligent diagnosis algorithms proposed recently and so on.

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Section: Short-time Fourier Transformmentioning

confidence: 99%

Section: Wavelet Transformmentioning

confidence: 99%

Faults and Diagnosis Methods of Permanent Magnet Synchronous Motors: A Review

et al. 2019

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“…In [14], wavelet analysis is used to extract the fault characteristics of the induction motor, which is better than the Fourier transform. In [15,16], wavelet analysis is also used in PMSM fault diagnosis. A method based on a variety of signals has been used in the fault diagnosis of induction motors [17].…”

Section: Introductionmentioning

confidence: 99%

Fault Detection of Stator Inter-Turn Short-Circuit in PMSM on Stator Current and Vibration Signal

et al. 2018

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The stator inter-turn short circuit fault is one of the most common and key faults in permanent magnet synchronous motor (PMSM). This paper introduces a time–frequency method for inter-turn fault detection in stator winding of PMSM using improved wavelet packet transform. Both stator current signal and vibration signal are used for the detection of short circuit faults. Two different experimental data from a three-phase PMSM were processed and analyzed by this time–frequency method in LabVIEW. The feasibility of this approach is shown by the experimental test.

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“…Moreover, electrical fault accounts for 38% of all motor faults. 5 Mechanical fault, which mainly includes bearing fault and rotor eccentric fault, is the most common type among the three types. The research shows that bearing fault accounts for 40%–50% of all the faults.…”

Section: Introductionmentioning

confidence: 99%

Mechanical faults detection for vehicle motors under nonstationary conditions based on Vold-Kalman order tracking method

Zhao

Song

Wang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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The fault diagnosis and health management of motors are the key technology that needs to be resolved in the future with the development of electric vehicles. The drive motors usually working under nonstationary conditions. Moreover, the mechanical fault is the most common type among the motor fault types. Therefore, developing the mechanical fault detection method under variable speed conditions would be of great value to improve the diagnosis accuracy of vehicle motors. This paper deals with the mechanism of the bearing fault, the rotor eccentricity fault, and their compound fault of permanent magnet synchronous motors. The purpose of this paper is to propose a mechanical fault detection method based on Vold-Kalman for vehicle motors under variable working conditions. First, the vibration characteristics of the healthy and the faulty motors are analyzed. Next, for eliminating the influence of variable conditions on the mechanical-fault detection, the fault characteristics are extracted by applying the Vold-Kalman filter. Finally, experiments are carried out based on the selected part of the new European driving cycle test conditions. The experimental results show that the proposed approach can detect the mechanical fault of the motor under nonstationary conditions effectively.

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Inter-Turn Fault Detection in Stator Winding of PMSM Using Wavelet Transform

Cited by 22 publications

References 7 publications

Faults and Diagnosis Methods of Permanent Magnet Synchronous Motors: A Review

Faults and Diagnosis Methods of Permanent Magnet Synchronous Motors: A Review

Fault Detection of Stator Inter-Turn Short-Circuit in PMSM on Stator Current and Vibration Signal

Mechanical faults detection for vehicle motors under nonstationary conditions based on Vold-Kalman order tracking method

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