Rotor cage fault diagnosis in induction motors based on spectral analysis of current Hilbert modulus

Abstract

Hilbert transformation is an ideal phase shifting tool in data signal processing. Being Hilbert transformed, the conjugated one of a signal is obtained. The Hilbert modulus is defined as the square of a signal and its conjugation. This work presents a method by which rotor faults of squirrel cage induction motors, such as broken rotor bars and eccentricity, can be diagnosed. The method is based on the spectral analysis of the stator current Hilbert Modulus of the induction motors. Theoretical analysis and experimental results demonstrate that has the same rotor fault detecting ability as the extended Park' vector approach. The vital advantage of the former is the smaller hardware and software spending compared with the existing ones.