A fault diagnosis method for induction motor rotors combining correlation analysis with phase difference correction

Abstract

Rotor faults are a prevalent failure mode in induction motors. In the stator current of induction motors, the fault characteristic frequency component is in close spectral proximity to the fundamental component, yet possesses an extremely low amplitude. This makes it prone to being overwhelmed by the leakage of the fundamental component and ambient noise. Accurate extraction of the fault characteristic component from the stator current is of great significance for the quantitative assessment of rotor faults. This paper proposes a detection method that leverages two-stage correlation analysis integrated with phase difference correction to suppress the fundamental component and noise, allowing for the precise extraction of the rotor fault frequency component. Results from simulations and experiments indicate that the proposed method effectively mitigates the impact of fundamental component leakage and retains robust detection accuracy under low signal-to-noise ratios.