Advanced Diagnosis of Electrical Faults in Wound-Rotor Induction Machines

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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“…), a set of new components at frequencies given by Equation (1) appear in the stator current spectrum [39][40][41]:…”

Section: Current Signature Analysismentioning

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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“…It is thus a powerful tool for condition monitoring and fault diagnosis. In this regard, intensive research efforts have focused on the use of approximation and detail signals for extracting the contribution of fault frequency components [10][11][12][13][14][15][16][17][18].…”

Section: -Time-frequency Domain Analysismentioning

confidence: 99%

On the Detection of Induction-Motor Rotor Fault by the Combined “Time Synchronous Averaging-Discrete Wavelet Transform” Approach

Ngote¹,

Ouassaid²,

Guedira³

et al. 2015

Journal of Electrical Engineering and Technology

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-Induction motors are widely used in industrial processes since they offer a very high degree of reliability. But like any other machine, they are vulnerable to faults, which if left unmonitored, might lead to an unexpected interruption at the industrial plant. Therefore, the condition monitoring of the induction motors have been a challenging topic for many electrical machine researchers. Indeed, the effectiveness of the fault diagnosis and prognosis techniques depends very much on the quality of the fault features selection. However, in induction-motor drives, rotor defects are the most complex in terms of detection since they interact with the supply frequency within a restricted band around this frequency, especially in the no-loaded case. To overcome this drawback, this paper deals with an efficient and new method to diagnose the induction-motor rotor fault based on the digital implementation of the monitoring algorithm based on the association of the Time Synchronous Averaging technique and Discrete Wavelet Transform. Experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the combined "Time Synchronous Averaging -Discrete Wavelet Transform" approach.

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“…In order to reach a good sensitivity (before calculating the signal energy) a pre-treatment of the tested signal is necessary to isolate the fault component into a frequency band wherein this component is the most prominent one; this is achieved by using or combining different signal analysis tools as Hilbert Transform (HT) [13], [16], [17], DWT [19], [20], CWT [14] or FS [21], [22].…”

Section: Index Terms--mentioning

confidence: 99%

Diagnosis of Rotor and Stator Asymmetries in Wound-Rotor Induction Machines Under Nonstationary Operation Through the Instantaneous Frequency

Vedreno-Santos

Riera-Guasp

Capolino

et al. 2014

IEEE Trans. Ind. Electron.

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Advanced Diagnosis of Electrical Faults in Wound-Rotor Induction Machines

Cited by 179 publications

References 44 publications

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

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

On the Detection of Induction-Motor Rotor Fault by the Combined “Time Synchronous Averaging-Discrete Wavelet Transform” Approach

Diagnosis of Rotor and Stator Asymmetries in Wound-Rotor Induction Machines Under Nonstationary Operation Through the Instantaneous Frequency

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