A Method for Detecting Half-Broken Rotor Bar in Lightly Loaded Induction Motors Using Current

Naha, Arunava; Samanta, Arunkumar; Routray, Aurobinda; Deb, Alok Kanti

doi:10.1109/tim.2016.2540941

Cited by 111 publications

(70 citation statements)

References 65 publications

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“…Let us consider the interference-free signal y computed by (18). When the noise variance is unknown, the matched subspace detector decides H 1 if [23] T…”

Section: A Exact Fault Detectormentioning

confidence: 99%

“…In case of faults, additional frequency components also appear in the current spectrum. To reveal these additional components, several spectral analysis techniques can be used such as the FFT [17], MUSIC [18], [19], and ESPRIT algorithms [10], [20]. However, these general spectral estimators do not exploit the particular spectrum structure induced by the fault.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, we propose a new matched subspace detector that treats the supply frequency components as an interference signal. To remove the supply frequency component, the authors in [18] have proposed a Kalman-based technique. However, this technique is suboptimal from a statistical sense when the fundamental frequency is quasi-stationary (i.e.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Motor Current Signal Analysis Based on a Matched Subspace Detector

Elbouchikhi

Choqueuse

Auger

et al. 2017

IEEE Trans. Instrum. Meas.

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International audience—Motor current signature analysis (MCSA) is a well-proven technique for electrical and mechanical faults detection in induction motors. The appearance of stator current components or increase of magnitude of some components at characteristic frequencies indicates a motor fault condition. In this paper, we propose a new MCSA fault detector based on a matched subspace technique. The proposed detector consists of three steps. First, the influence of the fundamental supply frequency is removed from the current signal using an interference cancellation technique based on oblique projection. Then, the fault-related frequency is estimated from the interference-free signal using the maximum likelihood (ML) principle. Finally, the fault detection is performed using a generalized likelihood ratio test. Simulation and experimental results illustrate the effectiveness of the proposed approach for eccentricity fault, bearing faults and broken rotor bars detection

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“…Let us consider the interference-free signal y computed by (18). When the noise variance is unknown, the matched subspace detector decides H 1 if [23] T…”

Section: A Exact Fault Detectormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Motor Current Signal Analysis Based on a Matched Subspace Detector

Elbouchikhi

Choqueuse

Auger

et al. 2017

IEEE Trans. Instrum. Meas.

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show abstract

“…Major mechanical faults are bearing fault [3][4][5] and broken rotor bar [6][7][8][9][10]. Electrical fault is influenced by power quality supplied by AC grid, frequency variations, voltage disturbances, and load variation.…”

Section: Introductionmentioning

confidence: 99%

Induction Motor Stator Interturn Short Circuit Fault Detection in Accordance with Line Current Sequence Components Using Artificial Neural Network

Rajamany

Srinivasan

Rajamany

et al. 2019

Journal of Electrical and Computer Engineering

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The intention of fault detection is to detect the fault at the beginning stage and shut off the machine immediately to avoid motor failure due to the large fault current. In this work, an online fault diagnosis of stator interturn fault of a three-phase induction motor based on the concept of symmetrical components is presented. A mathematical model of an induction motor with turn fault is developed to interpret machine performance under fault. A Simulink model of a three-phase induction motor with stator interturn fault is created for extraction of sequence components of current and voltage. The negative sequence current can provide a decisive and rapid monitoring technique to detect stator interturn short circuit fault of the induction motor. The per unit change in negative sequence current with positive sequence current is the main fault indicator which is imported to neural network architecture. The output of the feedforward backpropagation neural network classifies the short circuit fault level of stator winding.

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“…The causes of rotor bar faults include excessive dynamic load stress, electromagnetic stress due to imbalance in the stator's magnetic field, corrosion due to chemicals in the environment [3], etc. The consequences of BRB defect are increased vibration and noise, deterioration of the motor output efficiency, and early IM failure [4]. Since BRB faults will modulate the stator current signal, motor current signature analysis (MCSA) is more suitable in this fault detection than using vibration analysis.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive EMD Technique for Induction Motor Fault Detection

Mahmud¹,

Wang²

2019

JSIP

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Reliable induction motor (IM) fault detection techniques are very useful in industries to diagnose IM defects and improve operational performance. An adaptive empirical mode decomposition (EMD) technology is proposed in this paper for rotor bar fault detection in IMs. As the characteristic fault frequency will change with operating conditions related to load and speed, the proposed adaptive EMD technique correlates fault features over different frequency bands and intrinsic mode function (IMF) sidebands. The adaptive EMD technique uses the first IMF to detect the fault type and the second IMF as an indicator to predict the fault severity. It can overcome the problems of the sensitivity of sideband frequencies related to the speed and load oscillations. The effectiveness of the proposed adaptive EMD technique is verified by experimental tests under different motor conditions.

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A Method for Detecting Half-Broken Rotor Bar in Lightly Loaded Induction Motors Using Current

Cited by 111 publications

References 65 publications

Motor Current Signal Analysis Based on a Matched Subspace Detector

Motor Current Signal Analysis Based on a Matched Subspace Detector

Induction Motor Stator Interturn Short Circuit Fault Detection in Accordance with Line Current Sequence Components Using Artificial Neural Network

An Adaptive EMD Technique for Induction Motor Fault Detection

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