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Article Dans Une Revue International Journal on Energy Conversion Année : 2015

Induction Machine Diagnosis using Stator Current Advanced Signal Processing

Résumé

Induction machines are widely used in industrial applications. Safety, reliability, efficiency and performance are major concerns that direct the research activities in the field of electrical machines. Even though the induction machines are very reliable, many failures can occur such as bearing faults, air-gap eccentricity and broken rotor bars. Therefore, the challenge is to detect them at an early stage in order to prevent breakdowns. In particular, stator current-based condition monitoring is an extensively investigated field for cost and maintenance savings. In fact, several signal processing techniques for stator current-based induction machine faults detection have been studied. These techniques can be classified into: spectral analysis approaches, demodulation techniques and time-frequency representations. In addition, for diagnostic purposes, more sophisticated techniques are required in order to determine the faulty components. This paper intends to review the spectral analysis techniques and time-frequency representations. These techniques are demonstrated on experimental data issued from a test bed equipped with a 0.75 kW induction machine. Nomenclature O&M = Operation and Maintenance; WTG = Wind Turbine Generator; MMF = Magneto-Motive Force; MCSA = Motor Current signal Analysis; PSD = Power Spectral Density; FFT = Fast Fourier Transform; DFT = Discrete Fourier Transform; MUSIC = MUltiple SIgnal Characterization; ESPRIT = Estimation of Signal Parameters via Rotational Invariance Techniques; SNR = Signal to Noise Ratio; MLE = Maximum Likelihood Estimation; STFT = Short-Time Fourier Transform; CWT = Continuous Wavelet Transform; WVD = Wigner-Ville distribution; HHT = Hilbert-Huang Transform; DWT = Discrete Wavelet Transform; EMD = Empirical Mode Decomposition; IMF = Intrinsic Mode Function; AM = Amplitude Modulation; FM = Frequency Modulation; IA = Instantaneous Amplitude; IF = Instantaneous Frequency; í µí±“ ! = Supply frequency; í µí±“ ! = Rotational frequency; í µí±“ ! = Fault frequency introduced by the modified rotor MMF; í µí±“ ! = Characteristic vibration frequencies; í µí±“ !"# = Bearing defects characteristic frequency; í µí±“ !" = Bearing outer raceway defect characteristic frequency; í µí±“ !" = Bearing inner raceway defect characteristic frequency; í µí±“ !" = Bearing balls defect characteristic frequency; í µí±“ !"" = Eccentricity characteristic frequency; í µí± ! = Number of rotor bars or rotor slots; í µí± = Slip; í µí°¹ ! = Sampling frequency; í µí± = Number of samples; í µí±¤[. ] = Time-window (Hanning, Hamming, etc.); í µí¼ = Time-delay; í µí¼Ž ! = Variance; ℎ[. ] = Time-window.
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Dates et versions

hal-01249256 , version 1 (30-12-2015)

Identifiants

  • HAL Id : hal-01249256 , version 1

Citer

El Houssin El Bouchikhi, Vincent V. Choqueuse, Mohamed Benbouzid. Induction Machine Diagnosis using Stator Current Advanced Signal Processing. International Journal on Energy Conversion, 2015, 3 (3), pp.76-87. ⟨hal-01249256⟩
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