Indicator for bearing fault detection in asynchronous motors using stator current spectral analysis
Résumé
This paper deals with the application of motor current spectral analysis for the detection of artificially damaged rolling bearings in asynchronous machine. Vibration monitoring of mechanical characteristic frequencies related to the bearings is widely used to detect faulty operations. However, vibration measurement is expensive and can not always be performed. An alternative is to base the monitoring on the available electrical quantities e.g. the machine stator current which is often already measured for control and protection purposes. The bearing faults reveal the presence of mechanical load torque oscillations. A theoretical stator current model in case of load torque oscillations demonstrates the presence of phase modulation. Related sideband components appear in the current spectrum and can be used for detection. Experimental measurements show that their amplitudes are linked to the fault frequency by a transfer function including resonance. This singularity will be used to improve the detection efficiency. Fault detectors using the energy of stator current in specific frequency ranges are then proposed. The efficiency of indicators is studied on long and short data records of experimental current for different bearing faults. The most significant of the investigated indicators is finally improved to guarantee a higher reliability of the detection.
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