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 1.5kW three-phase squirrel-cage induction motor. Their generalisation abilities have been tested through the data collected with a 3kW induction motor.
neural networks load torque monitoring induction motor supervised and unsupervised learning algorithms multi-layer perceptron kohonen self-organised map