Identification of False Rotor Fault Indications Produced by Online MCSA for Medium-Voltage Induction Machines

Lee, Sang Bin; Hyun, Doosoo; Kang, Tae June; Yang, Changwon; Shin, Sung-Sik; Kim, Heonyoung; Park, Sungbong; Kong, Tae‐Sik; Kim, Hee‐Dong

doi:10.1109/tia.2015.2464301

Cited by 79 publications

(43 citation statements)

References 32 publications

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“…It can thus be inferred that the existing methods presented in References [10][11][12][13][14][15] would perforce fail in the most adverse case that f L were absolutely equal to 2sf s . This problem has also been reported and addressed in References [16,17].…”

Section: Drawbackmentioning

confidence: 57%

“…Significant attention has been paid to the detection of broken rotor bar (BRB) faults in induction motors [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. The spectral analysis of the stator current has been widely applied to detect BRB faults [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…It has been widely recognized that load oscillation, of which the frequency f L is next to 2sf s , produces similar effects as BRB fault on the stator current and thus confuses the BRB fault detection based on the spectral analysis of the stator current [10][11][12][13][14][15][16][17]. Therefore, the issue of discerning BRB fault and load oscillation must be addressed.…”

Section: Introductionmentioning

confidence: 99%

“…Time-frequency analysis of the startup current was also used in Reference [16], requiring a motor startup that should not be too short. Similarly, offline methods, for example, at standstill and manual rotation of the rotor, were recommended in Reference [15,17]. Certainly, all these methods are lack of practicability from the engineering point of view.…”

Section: Introductionmentioning

confidence: 99%

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An Improved Method for Discerning Broken Rotor Bar Fault and Load Oscillation in Induction Motors

Sun

2018

Energies

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A few methods for discerning broken rotor bar (BRB) fault and load oscillation in induction motors have been reported in the literature. However, they all perhaps inevitably fail in adverse cases in which these two phenomena are simultaneously present. To tackle this problem, an improved method for discerning BRB fault and load oscillation is proposed in this paper based on the following work. On the one hand, the theoretical basis is analytically extended to include such an adverse case, yielding some important findings on the spectra of the instantaneous reactive and active powers. A novel strategy is thus outlined to correctly discern BRB fault and load oscillation even when simultaneously present. On the other hand, Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) is adopted as the spectral analysis technique to deal with the instantaneous reactive and active powers, yielding a certain improvement compared to the existing methods, adopting Fast Fourier Transform (FFT). Simulation and experimental results demonstrate that the proposed method can correctly discern BRB fault and load oscillation even when simultaneously present.

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Section: Drawbackmentioning

confidence: 57%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Improved Method for Discerning Broken Rotor Bar Fault and Load Oscillation in Induction Motors

Sun

2018

Energies

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“…Motor current signature analysis(MCSA) [7] is the most widely spread approach for condition monitoring, especially for mechanical faults [8]. MCSA requires measurement and processing of the stator currents to identify any abnormality in the machines by detecting changes in the harmonic content.…”

mentioning

confidence: 99%

Fault Signal Propagation Through the PMSM Motor Drive Systems

Sumner

Padilla

et al. 2017

IEEE Trans. on Ind. Applicat.

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract -This paper describes how a mechanical disturbance on the shaft of a variable speed permanent magnet motor (PMSM) is propagated to the supply input side of the drive system, and therefore may be detected by monitoring specific frequency components in the rectifier input current. The propagation of the disturbance from the torque disturbance, to the motor current, then to the dc link current and finally to the rectifier input current is derived as a series of transfer functions so that both the frequency and the amplitude of the disturbance component in the rectifier input current can be predicted for a specific mechanical disturbance. The limitations to detect the mechanical fault by monitoring only the supply currents are also addressed. Simulation and experimental results are presented to demonstrate the accuracy of the quantitative analysis, and the potential for fault detection using the rectifier input currents.

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A Histogram of Oriented Gradients for Broken Bars Diagnosis in Squirrel Cage Induction Motors

Silva

Dias

Alves

2018

Artificial Neural Networks and Machine Learning – ICANN 2018

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Identification of False Rotor Fault Indications Produced by Online MCSA for Medium-Voltage Induction Machines

Cited by 79 publications

References 32 publications

An Improved Method for Discerning Broken Rotor Bar Fault and Load Oscillation in Induction Motors

An Improved Method for Discerning Broken Rotor Bar Fault and Load Oscillation in Induction Motors

Fault Signal Propagation Through the PMSM Motor Drive Systems

A Histogram of Oriented Gradients for Broken Bars Diagnosis in Squirrel Cage Induction Motors

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