Motor bearing damage detection using stator current monitoring

Schoen, R.R.; Habetler, T.G.; Kamran, F.; Bartfield, R.G.

doi:10.1109/ias.1994.345491

Cited by 285 publications

(167 citation statements)

References 4 publications

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“…A reciprocating compressor system consists of an induction motor, in which the compressor has two basic working processes including compression and expansion. The working process gives rise to a periodically varying load to the driving motor due to the compressor requiring more power in compression than in expansion [26]. This varying load leads to high oscillation in the measured current signal.…”

Section: Motor Current Signalmentioning

confidence: 99%

Phase-compensation-based dynamic time warping for fault diagnosis using the motor current signal

Zhen¹,

Zhao²,

Gu³

et al. 2012

Meas. Sci. Technol.

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Abstract. Dynamic Time Warping (DTW) is a time domain based method and widely used in various similar recognition and data mining applications. This paper presents a phase compensation based DTW to process the motor current signals for detecting and quantifying various faults in a two-stage reciprocating compressor under different operating conditions. DTW is an effective method to align up two signals for dissimilarity analysis. However, it has drawbacks such as singularities and high computational demands that limit its application in processing motor current signals for obtaining modulation characteristics accurately in diagnosing compressor faults. Therefore, a phase compensation approach is developed to reduce the singularity effect and a sliding window is designed to improve computing efficiency. Based on the proposed method, the motor current signals measured from the compressor induced with different common faults are analysed for fault diagnosis. Results show that residual signal analysis using the phase compensation based DTW allows the fault related sideband features to be resolved more accurately for obtaining reliable fault detection and diagnosis. It provides an effective and easy approach to the analysis of motor current signals for better diagnosis in the time domain in comparison with conventional Fourier Transform based methods.

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Section: Motor Current Signalmentioning

confidence: 99%

Phase-compensation-based dynamic time warping for fault diagnosis using the motor current signal

Zhen¹,

Zhao²,

Gu³

et al. 2012

Meas. Sci. Technol.

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“…Finite Element Analysis of three phase Induction motor: comparisons of two different approaches deals with fault analysis of Induction motor using finite element analysis [6]. Bearing damage detection using stator current monitoring explains in detail about the detection of bearing fault using MCSA method [7]. Online diagnosis of Induction motors using MCSA explains the identification of fault [8].Vibration and current monitoring for detecting airgap eccentricity in large Induction motors explain about the air-gap eccentricity and its fault detection methods [9].…”

Section: Literature Surveymentioning

confidence: 99%

Modeling and Simulation of Faulty Squirrel Cage Induction Motor Using Magnet

Nagarajan¹,

Reddy²

2010

IJCEE

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Abstract-Induction motors are widely used in industry as prime electro mechanical energy conversion devices. Consequently the condition monitoring and fault diagnosis of induction motors have received significant attention recently and become an integrated part of various maintenance strategies. This paper presents the modeling and simulation of fault diagnosis of 3-phase squirrel-cage induction motor using magnet. The cross section of the machine was modeled with finite elements, and the field distribution and magnetic performance were computed. The fault considered in this work is broken bar condition. Simulation is performed using magnet and the results are presented.

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“…It is based on the effect that the changes in the air gap between the stator and the rotor have on the spatial magnetic field lines. The congruency of vibrational harmonics and current harmonic caused by abnormal bearings was reported in 1995 (3) . In addition to enabling the detection of bearing abnormalities, it has been discovered theoretically that it is possible to detect current harmonics c 2018 The Institute of Electrical Engineers of Japan.…”

Section: Introductionmentioning

confidence: 99%

Bearing Fault Detection in Induction Machine Based on Stator Current Spectrum Monitoring

et al. 2018

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Bearing faults account for a large majority of the faults in a three-phase induction motor. Recently, many research activities were focused on the diagnosis of bearing faults by motor current signature analysis. However, the effective frequency band is not fully understood in terms of the diagnosis of the bearing fault. Moreover, the temporal change in motor stator current spectrum with faulty bearing has not been sufficiently investigated. The purpose of this paper is to clarify the characteristic frequency band and to evaluate the temporal change in the power spectral density of stator current by using powder contaminated bearing before complete halt of the motor. Experiments were performed with normal and powder contaminated bearings in the induction motor. The diagnosis technique for the powder contaminated bearing is discussed based on the experimental results.

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Motor bearing damage detection using stator current monitoring

Cited by 285 publications

References 4 publications

Phase-compensation-based dynamic time warping for fault diagnosis using the motor current signal

Phase-compensation-based dynamic time warping for fault diagnosis using the motor current signal

Modeling and Simulation of Faulty Squirrel Cage Induction Motor Using Magnet

Bearing Fault Detection in Induction Machine Based on Stator Current Spectrum Monitoring

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