Alternator Rotor Inter-turn Short-Circuit Identification using FEM Based Learning

摘要

The goal of this paper is to identify rotor inter-turn short-circuits of an alternator. The detection method is based on the analysis of a flux probe signal located in the air gap of the machine. Previous works have shown that pattern recognition can be applied to detect such a fault by using the experimental data as prototypes. A new method is developed here by considering a learning step based on simulation. Therefore the machine is modeled and validated in that purpose. A feature selection is made by considering feature correlation and disparity. Finally, k nearest neighbors is used to classified experimental test data.