Induction Motor Failure Detection Using Geometric Signal Separation

Abstract

We present a new method for on-line induction motor failure detection using stator current monitoring. The concept of geometric signal separation in feature space is introduced. A set of observations from a single phase of the stator current is transformed into a feature vector. After establishing a local metric in the feature space, close neighbors of the present vector are searched for in a database representing allowed states of the motor, which were recorded during a training period. In their absence the present state is a novelty, which is considered as a failure if it persists for a certain time. This monitoring scheme successfully deals with varying load conditions of the motor, where also oscillating load torques can be tackled. Additionally, observations from a healthy motor, which differ considerably from any known allowed state in the database due to changes of environmental conditions can be distinguished from true failures at a significant level. We do not use expert rules or detailed knowledge about the monitored motor.