Advanced diagnosis of rotor faults and eccentricity in induction motors based on internal flux measurement

Most of the existing electrical techniques of condition monitoring and fault diagnosis are based on frequency analysis of signals measured externally to the motor. In this paper, it is proposed to add the space dimension to the measured signals by using an array of Hall effect flux sensors installed inside the motor air gap, and to explore the advantages brought by such an instrumentation. The paper presents analytical models of air gap flux density expressed in terms of time and space, for a healthy motor and for a motor with rotor bar faults and mixed eccentricity. Based on these models, the paper proposes a new technique for early detection of rotor bar faults and mixed eccentricity, and for discrimination between them. The paper demonstrates that, with the help of the proposed technique, the severity of each fault and its location relative to rotor or stator can be accurately established. The results of the presented study are supported by simulations and validated by experiments on a laboratory scale induction motor. The formulated fault diagnosis algorithm is suitable for real-time implementation.