Comprehensive Diagnostics of Induction Motor Faults Based on Measurement of Space and Time Dependencies of Air Gap Flux

Abstract

Condition monitoring of induction motors is important for their efficient and reliable operation. Most of the existing electrical techniques of condition monitoring and fault diagnosis are based on current, voltage, vibration, or/and flux measurements external to the motor. This paper proposes an online fault diagnostic system, which is based on measurements of internal main air gap flux density of an induction motor by an array of Hall effect flux sensors. Such an instrumentation is justified for large specialized induction motors with particularly high-reliability requirements. Fundamental theory behind the air gap flux density as a function of time and space, and its distortions introduced by various faults, is reviewed in this paper. Based on this theory, this paper proposes a comprehensive condition monitoring approach to diagnose induction motor faults including stator turn-to-turn shorts, rotor bar damage, and static and dynamic eccentricity, which may be present individually or at the same time. Moreover, the proposed approach not only detects each fault at its early stage but also determines its exact location and severity. The principles proposed in this paper are illustrated by extensive simulations and are experimentally validated on a prototype online condition monitoring system based on National Instruments real-time platform.