Neural networks for load torque monitoring of an induction motor

In this paper, the possibility to use neural networks for the monitoring of the load torque of induction motors is investigated. In particular, unsupervised neural networks are used to detect possible torque anomalies and supervised neural networks are used to identify the average value of steady-state load torque. These networks are trained and validated on the data gathered from a 1.5 kW three-phase squirrel-cage induction motor. Their generalisation abilities have been tested through the data collected with a 3 kW induction motor.