Dynamical models for fault detection in squirrel cage induction motors

Abstract: Induction motors are the dominant components in industrial processes involving electromechanical energy conversion. Safety, reliability and efficiency are major concerns in modern induction motor applications. Since detecting faults on time could avoid costly unscheduled shutdowns, in recent years there has been an increased interest in induction motor fault detection and diagnosis. In this paper, we propose monitoring schemes to solve fault detection problems of induction motors. We begin with a monitoring scheme to detect detuning operation in Indirect Field Oriented Control (IFOC) driven induction motors. Secondly, we present a monitoring scheme to detect broken rotor bars on IFOC-driven induction motors. The proposed monitoring scheme does not rely on spectral methods; instead, it monitors a carefully selected induction motor state, using an online observer. The key to fault detection is the development of a simplified dynamic model of a squirrel cage induction motor with broken rotor bars. Numerical simulations validate both monitoring schemes.