Performance-Oriented Electric Motors Diagnostics in Modern Energy Conversion Systems

Choi, Seungdeog; Akin, Bilal; Rahimian, Mina M.; Toliyat, H.A.

doi:10.1109/tie.2011.2158037

Cited by 42 publications

(13 citation statements)

References 33 publications

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“…In Fig. 9(b), six selected noise frequency signatures are shown, which are at the frequencies expecting no fundamental harmonics current and any other fault frequencies based on MCSA theory [5], [6]. Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Time-demanding fault diagnosis of electric machines has been investigated to identify the indication of incipient failure symptoms to prevent catastrophic failures [2]- [4]. One of the promising diagnosis strategies in recent years has been known as motor current signature analysis (MCSA) [5], [6] as the motor signal is readily available from a motor control service routine without extra hardware or design cost [7]. The motor current signal provides superior information to the vibration signature in terms of error rate under different operating conditions such as speed [8] and load torque variation [9].…”

Section: Introductionmentioning

confidence: 99%

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Iterative Condition Monitoring and Fault Diagnosis Scheme of Electric Motor for Harsh Industrial Application

Choi

Pazouki

Baek

et al. 2015

IEEE Trans. Ind. Electron.

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This paper presents a robust diagnosis technique by iteratively analyzing the pattern of multiple fault signatures in a motor current signal. It is mathematically and experimentally proved that the proposed diagnosis algorithm provides highly accurate monitoring performance while minimizing both false detection and miss detection rate under high noise and nonlinear machine operating condition. These results are verified on a digital-signal-processor-based motor drive system where motor control and fault diagnosis are performed in real time.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Iterative Condition Monitoring and Fault Diagnosis Scheme of Electric Motor for Harsh Industrial Application

Choi

Pazouki

Baek

et al. 2015

IEEE Trans. Ind. Electron.

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“…Generator bearing and eccentricity, as well as pinion gear faults, can automatically be detected through stator current analysis using information entropy [20], through an adaptive neuro-fuzzy inference system and particle filtering [21] or computing the energy from the fault-related frequencies [22,23]. The results are validated at laboratory benches for the studies in [20][21][22][23] and using simulated data in [24,25]. The main drawback of these approaches is the need for a healthy current baseline.…”

Section: Fault Diagnosis Techniques For Drive Trains and Induction Gementioning

confidence: 99%

Current Signature and Vibration Analyses to Diagnose an In-Service Wind Turbine Drive Train

Artigao

Koukoura

Carroll³

et al. 2018

Energies

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Abstract:The goal of the present paper is to achieve the diagnosis of an in-service 1.5 MW wind turbine equipped with a doubly-fed induction generator through current signature and vibration analyses. Real data from operating machines have rarely been analysed in the scientific literature through current signature analysis supported by vibrations. The wind turbine under study was originally misdiagnosed by the operator, where a healthy component was replaced and the actual failure continued progressing. The chronological evolution of both the electrical current and vibration spectra is presented to conduct an in-depth tracking of the fault. The diagnosis is achieved through spectral analysis of the stator currents, where fault frequency components related to rotor mechanical unbalance are identified. This is confirmed by the vibration analysis, which provides insightful information on the health of the drive train. These results can be implemented in condition monitoring strategies, which is of great interest to optimise operation and maintenance costs of wind farms.

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“…Research shows that it is of great significance to set a temperature protection limit and to increase the response speed of overheating failure protection for an induction motor [5], [6]. As a matter of fact, there are many factors that affect the accuracy and efficiency of the identification of temperature, such as the uncertainty of the harmonic order, the complexity of the motor parameters, and most of all, the stator voltage transient shock [7]- [11].…”

Section: Introductionmentioning

confidence: 99%

An Approach for Identifying the Temperature of Inductance Motors by Estimating the Rotor Slot Harmonic Based on Model Predictive Control

Wang¹,

Jiang²,

Zhang³

et al. 2017

Journal of Power Electronics

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In order to satisfy the urgent requirements for the overheating protection of induction motors, an approach that can be used to identify motor temperature has been proposed based on the rotor slots harmonic (RSH) in this paper. One method to accomplish this is to improve the calculation efficiency of the RSH by predicting the stator winding distribution harmonic order by analyzing the harmonics spectrum. Another approach is to increase the identification accuracy of the RSH by suppressing the influence of voltage flashes or current surges during temperature estimation based on model predictive control (MPC). First, an analytical expression of the stator inductance is extracted from a steady-state positive sequence motor equivalent circuit model developed from the rotor flux field orientation. Then a procedure that applies MPC for reducing the identification error of the rotor temperature caused by voltage sag or swell of the power system is given. Due to this work, the efficiency and accuracy of the RSH have been significantly improved and validated our experiments. This work can serves as a reference for the on-line temperature monitoring and overheating protection of an induction motor.

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Performance-Oriented Electric Motors Diagnostics in Modern Energy Conversion Systems

Cited by 42 publications

References 33 publications

Iterative Condition Monitoring and Fault Diagnosis Scheme of Electric Motor for Harsh Industrial Application

Iterative Condition Monitoring and Fault Diagnosis Scheme of Electric Motor for Harsh Industrial Application

Current Signature and Vibration Analyses to Diagnose an In-Service Wind Turbine Drive Train

An Approach for Identifying the Temperature of Inductance Motors by Estimating the Rotor Slot Harmonic Based on Model Predictive Control

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