Inter-Turn Stator Winding fault Diagnosis for Permanent Magnet Synchronous Motor based Power Spectral Density Estimators

Zerdani, Sara; Hafyani, M. L. El; Zouggar, Smail

doi:10.1109/icsgce49177.2020.9275606

Cited by 2 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The following parameters ( M a1a2 and M a2b ) are respectively the mutual inductances between the windings (as2, as1) and the windings (as2, bs) resulting from the new stationary magnetic field, which can be identified based on the Finite Element Method (FEM) [13].…”

Section: Pmsm's Dynamic Model In (˛ˇ) Reference Frame With Itsfmentioning

confidence: 99%

Application of power spectral density and the support vector machine to fault diagnosis for permanent magnet synchronous motor

Zerdani¹,

Elhafyani²,

Zouggar³

2022

SN Appl. Sci.

Self Cite

View full text Add to dashboard Cite

The present study proposes a new technique for diagnosing the Inter-Turn Stator-Winding fault in Permanent Magnet Synchronous Motors. Under faulty operating conditions, the system’s model is built while considering specific parameters linked to fault location and sharpness. The proposed fault-detection method is principally based on the Power Spectral Density estimator’s association with the Support Vector Machine. This classifier is used to separate different regions of system performance. It has been trained to associate the Power Spectral Density current’s magnitude and the stator’s current negative sequence with the fault severity. This method has shown exceptional performance as long as it achieves a fault detection rate of 98.5% for different fault severities. Two Power Spectral Density estimators were compared in terms of their ability to extract fault characteristics, namely Burg’s method and Welch’s method. It was concluded from this study that Welch’s has a higher frequency resolution than Burg’s method.

show abstract

Section: Pmsm's Dynamic Model In (˛ˇ) Reference Frame With Itsfmentioning

confidence: 99%

Application of power spectral density and the support vector machine to fault diagnosis for permanent magnet synchronous motor

Zerdani¹,

Elhafyani²,

Zouggar³

2022

SN Appl. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

Review of Methods for Diagnosing Faults in the Stators of BLDC Motors

2022

View full text Add to dashboard Cite

A brushless direct current (BLDC) motor is a type of permanent magnet machine that is highly efficient and powerful and requires occasional maintenance. Thanks to these fortunate characteristics, this type of motor has various applications in high-tech industries. However, since BLDC motors are often required to operate at high-speed rotations and under extreme conditions, temperature overshoots can appear during operation, provoking damage to the windings. The purpose of this review is to present the results of a recent investigation and recollection of different methods used for the diagnosis of electrical faults in the stator, such as turn-to-turn short circuits, coil-to-coil short circuits, phase-to-phase short circuits and phase open circuits. In particular, this review presents an analysis of the available diagnosis methods according to the type of fault, the method or technique used for the diagnosis, the evaluated physical variables and the context in which the methods were evaluated (in simulations or in experimental tests). Based on this analysis, the following classifications of diagnostic methods are proposed: signal-based, model-based and data-based methods. Then, the pros and cons of each method class are described and discussed.

show abstract

Inter-Turn Stator Winding fault Diagnosis for Permanent Magnet Synchronous Motor based Power Spectral Density Estimators

Cited by 2 publications

References 8 publications

Application of power spectral density and the support vector machine to fault diagnosis for permanent magnet synchronous motor

Application of power spectral density and the support vector machine to fault diagnosis for permanent magnet synchronous motor

Review of Methods for Diagnosing Faults in the Stators of BLDC Motors

Contact Info

Product

Resources

About