This paper presents a methodology for winding stator fault
detection of induction motors, using an external search coil, which is a noninvasive
technique and can be applied during motor operation. The
dispersion magnetic flux of the motor operating in abnormal conditions
induces a voltage in the search coil that differs from a reference pattern
corresponding to the healthy stator winding. Experimental data were
obtained in a test bench using a 0.75 kW three-phase squirrel-cage induction
motor with the stator winding modified to allow the introduction of short
circuits. This work considered short circuits in one phase, involving 1%, 3%,
5% and 10% of the turns, with the motor loaded with a varying torque. Fault
diagnosis is obtained through two models of artificial neural networks,
implemented with the signals in the time domain. The obtained results
demonstrated that the developed methodology presents difficulties in
predicting short circuits in incipient stages, but for short circuits of higher
severity, the behaviour improved substantially, being 100% successful for
faults with 10% turns short-circuited.
This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020.
