Square current space-vector signature analysis for rotor fault detection in wound-rotor induction machine

Abstract

Fault detection in induction machines is commonly realized through motor current signature analysis. In case of Wound-Rotor Induction Machine rotor faults, the amplitude of the inverse sequence harmonic component -sf of the rotor current space-vector is monitored in order to sense its variation. However, motor current signature analysis is limited by some drawbacks. In fact, under transient operating conditions an efficient Fast Fourier Transform cannot be made, since slip or frequency vary, and so the amplitude of the harmonic component -sf. In this paper, a new technique based on the Square Current Space-vector Signature Analysis (SCSSA) is proposed for rotor fault detection in Wound-Rotor Induction Machines operating under time-varying conditions. The performance of the proposed approach is confirmed by simulation and experimental results. The proposed technique can be easily embedded in the digital control system for modern wind power plants.