This paper addresses the problem of the real time rebuilding of the load torque disturbances in asynchronous machines. Since the load pattern modifies the motor's supply current, it should be possible to use the current pattern to rebuild torque pattern, utilizing the machine itself as a torque sensor. In the paper the problem is studied utilizing both relationships developed under simplifying assumptions and a more complex model of the machine. The results obtained are compared with the experimental ones. Reference is made to low frequency torque disturbances, that cause a quasi-stationary machine behavior. It is shown that a Neural Network approach can be an alternative and efficient method for the torque pattern recognition.
Monitoring of induction machines load torque disturbances: An alternative NN-based method / Filippetti, F.; Grellet, G.; Salles, G.; Franceschini, G.; Tassoni, C.. - 1:(1998), pp. 103-110. (Intervento presentato al convegno Proceedings of the 1998 IEEE Industry Applications Conference. Part 1 (of 3) tenutosi a St.Louis, MO, USA, null nel 1998).
Monitoring of induction machines load torque disturbances: An alternative NN-based method
Franceschini, G.;
1998
Abstract
This paper addresses the problem of the real time rebuilding of the load torque disturbances in asynchronous machines. Since the load pattern modifies the motor's supply current, it should be possible to use the current pattern to rebuild torque pattern, utilizing the machine itself as a torque sensor. In the paper the problem is studied utilizing both relationships developed under simplifying assumptions and a more complex model of the machine. The results obtained are compared with the experimental ones. Reference is made to low frequency torque disturbances, that cause a quasi-stationary machine behavior. It is shown that a Neural Network approach can be an alternative and efficient method for the torque pattern recognition.
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