Modelling and Diagnostic of Incipient Stator Inter-turn Short Circuit Fault in Induction Motors

In this paper, a new modelling approach using finite element method is presented which enables detailed simulation (two turn-to-turn resolution) of the induction motor (IM) and insulation degradation. The benefit of this approach is that it enables virtual testing to simulate different fault types and fault locations under different motor loading conditions. One can apply the fault to any number of turns and any slot and phase as desired. One can also set the fault severity to reflect the extent of insulation deterioration. The proposed modelling technique is then verified by experimental testing on an actual motor setup in the laboratory. Also, in spite of existing methods for identification of stator winding insulation failure (SWIF) in IMs, a condition monitoring system that is capable of detecting insulation deterioration at its early stage is still lacking. The ability of the Second Order Generalized Integrator-Adaptive Notch Filter (SOGI-ANF) in extracting the main power frequency component and the so-called total harmonic signal makes it a very effective tool for use in signal processing algorithm for fault detection. This will be used in this paper for SWIF identification and fault location. With the support of signal processing and modelling techniques, it is revealed that the fault can be detected within a fraction of second after its occurrence. Moreover, after detecting the fault it is imperative to find the physical location of the SWIF. The task includes not only identifying the faulted phase but also discriminating between healthy and faulty stator slots. SOGI-ANF along with FEM is employed to precisely locate the SWIF.