Stator inter‐turn faults diagnosis in induction motors using zero‐sequence signal injection

Otero, Marcial; Barrera, Pablo M. de la; Bossio, Guillermo R.; Leidhold, Roberto

doi:10.1049/iet-epa.2020.0461

Cited by 6 publications

(5 citation statements)

References 52 publications

(67 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results presented in [52] show good performance in detecting the aforementioned damage in terms of both location and severity of damage. Due to the fact that the vast majority of electrical machines are powered by power electronic converters, on-line methods of turn-to-turn faults based on control algorithms [53,54] and using zero-sequence signal injection [55] have been developed. Methods based on artificial intelligence and genetic algorithms are also often used to assess the technical condition of the insulation [56][57][58].…”

Section: Other Methodsmentioning

confidence: 99%

Methods of Diagnosing the Insulation of Electric Machines Windings

et al. 2022

View full text Add to dashboard Cite

The presented article concerns issues related to the diagnostics of the technical condition of the insulation of electrical machines. It discusses the importance of the operational supervision, maintenance and diagnostics of electrical machine insulation systems. The structure of the insulation system is presented and known solutions for making winding insulation are described. The negative impact of conditions and various exposures on the technical condition of the insulation system is described. Special attention is focused on the review of available diagnostic methods for insulating systems of electrical machines. These methods have been arranged in a systematic order according to the type of tests to be carried out.

show abstract

Section: Other Methodsmentioning

confidence: 99%

Methods of Diagnosing the Insulation of Electric Machines Windings

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In Equation (10), Y(k * ) is the value of the double-window apFFT at point k * ; F g (k * ∆ω − ω * ) is obtained from bringing (k * ∆ω − ω * ) into the Fourier transform of the window function. Generally, the window function is a cosine window, and its Fourier transform expression is determined.…”

Section: Apfft Time-shift Phase Difference Correction Algorithmmentioning

confidence: 99%

“…The inter-turn insulation is the weakest part of the asynchronous traction motor insulation system [9]. When an ITSC fault occurs, an interturn current circulates between the short-circuit turns, quickly producing a large amount of heat [10], which weakens the insulation of the motor and results in inter-phase or ground short-circuit faults [11]. Timely maintenance can prevent the ITSC fault's further expansion and significantly reduce the maintenance cost.…”

Section: Introductionmentioning

confidence: 99%

Stator ITSC Fault Diagnosis of EMU Asynchronous Traction Motor Based on apFFT Time-Shift Phase Difference Spectrum Correction and SVM

Liu

et al. 2023

Energies

View full text Add to dashboard Cite

EMU (electric multiple unit) traction motors are powered by converters whose output voltage increases the voltage stress borne by the insulation system, making the ITSC (inter-turn short-circuit) fault more prominent. An index based on short-circuit thermal power is proposed in the article to evaluate the non-metallic ITSC faults extent. The apFFT (all-phase FFT) time-shift phase difference correction with double Hanning windows is used to calculate fault features to train the SVM (support vector machine) fault diagnosis model whose hyper-parameters C and g are optimized using grid search methods. The experimental verification was carried out on the EMU electric traction simulation experimental platform. According to the fault extent index proposed in this article, the experimental samples were divided into three categories, normal, incipient and serious fault samples. The ITSC fault diagnosis accuracy was 100% on the training dataset and 93.33% on the test dataset. There was no misclassification between normal and serious ITSC fault samples.

show abstract

“…Sundaram and Toliyat [20] use DC voltage injection for monitoring and detection of inter-turn stator faults in five-phase induction motors, integrated into the control loop and allows the motor to smoothly transition from normal operation to fault-tolerant operation once the fault has been detected, with minimal modification of the control logic. The available literature aims, in general, to present the most prominent different techniques for detecting faults in the short circuit [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

The Fast Prognosis of Inter-Turn Faults in an Induction Motor

Bouaissi,

Rezig,

Touati

2023

MMEP

View full text Add to dashboard Cite

This paper introduces a novel approach for detecting and prognosing stator inter-turn faults in induction motors, addressing an important aspect of motor health monitoring. The most commonly employed method for fault detection in this context is Motor Current Signature Analysis (MCSA). By leveraging this method, the paper focuses on the generation of periodic Magneto Motive Force (MMF) waves in the balanced current signal as a result of inter-turn faults. These MMF waves serve as crucial indicators for identifying the presence of such faults. To achieve early detection and prognostic capability for inter-turn faults, the paper proposes a numerical model that relies on analyzing the forward and backward currents. This model offers a promising approach to effectively detect and prognose these faults before they escalate into more severe issues. The obtained results from applying the proposed method demonstrate its efficiency in fault detection and prognostic accuracy for stator inter-turn faults. To validate the effectiveness of the proposed approach, an experimental setup is implemented. This setup provides a real-world context for evaluating the performance and reliability of the method in detecting and prognosing inter-turn faults. Through this validation process, the paper strengthens the credibility and applicability of the proposed technique in practical motor maintenance and fault management scenarios.

show abstract

Stator inter‐turn faults diagnosis in induction motors using zero‐sequence signal injection

Cited by 6 publications

References 52 publications

Methods of Diagnosing the Insulation of Electric Machines Windings

Methods of Diagnosing the Insulation of Electric Machines Windings

Stator ITSC Fault Diagnosis of EMU Asynchronous Traction Motor Based on apFFT Time-Shift Phase Difference Spectrum Correction and SVM

The Fast Prognosis of Inter-Turn Faults in an Induction Motor

Contact Info

Product

Resources

About