Induction Machine Bearing Fault Detection by Means of Statistical Processing of the Stray Flux Measurement

Rolling bearing faults are generally slowly progressive; therefore, the development of an effective diagnostic technique could be worth detecting such faults in their incipient phase and preventing complete failure of the motor. The methods proposed in the literature for this purpose are mainly based on measuring and analyzing vibration and current. Here, a novel technique based on the stray flux measurement in different positions around the electrical machine is proposed. The main advantages of this method are due to the simplicity and the flexibility of the custom flux probe with its amplification and filtering stage. The flux probe can be easily positioned on the machines and adapted to a wide range of power levels. This paper also reports an extensive survey on the stray-flux-based fault detection methods for induction motors, prior to introducing a novel sensor/diagnostic scheme.