Induction Machine Diagnosis Using Stator Current Advanced Signal Processing


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Abstract


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 0.75kW induction machine.
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Keywords


Induction Machines; Condition Based Maintenance; Faults Detection; Signal Processing; Spectral Analysis

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