Dynamic eccentricity fault diagnosis in round rotor synchronous motors

In this paper, a novel approach is presented to detect dynamic eccentricity in round rotor synchronous motors. For this, an efficient index is introduced based on processing developed torque using time series data mining (TSDM) method. This index can be utilized to diagnose eccentricity fault and its degree. The capability of this index to predict dynamic eccentricity is illustrated by investigation of load variation impacts on the nominated index. Stator current spectrum of the faulty synchronous motor under different loads and dynamic eccentricity degrees are computed. Effects of the dynamic eccentricity and load variation simultaneously are scrutinized on the magnitude of 17th and 19th harmonic components as traditional indices for eccentricity fault diagnosis in synchronous motors. Necessity signals and parameters for processing and feature extraction are evaluated by winding function method which is employed to model healthy and faulty synchronous motors.

Research highlights
► We have presented a novel approach to detect dynamic eccentricity in round rotor synchronous motors.
► We have introduced an efficient index based on processing torque using time series data mining method.
► The stator current spectrum of the motor under different levels of fault and load are computed.
► Winding function method has been employed to model healthy and faulty synchronous motors.