A novel cooling condition monitoring method for induction motors based on particle swarm optimization

Prolonged induction motor operations under impaired cooling conditions can lead to overtemperature of motor components, which leads to accelerated degradation of motor windings, bearings and stator cores. This paper proposes a novel cooling condition monitoring method to detect and classify impaired cooling conditions. A second-order thermal model is used to characterize thermal behaviors of induction motors. Particle swarm optimization is applied to identify thermal parameters under the thermal transient. Impaired cooling conditions can be classified by observing the trend of changes in the identified stator and rotor thermal resistances. The proposed method has been validated by experiments on a 7.5-hp induction motor with open drip proof enclosure.