Title :
An Alternative Approach to Estimate Load Torque in Industrial Environment Using Neural Networks
Author :
Goedtel, A. ; da Silva, I.N. ; Serni, P. J A ; Flauzino, R.A.
Author_Institution :
Eng. Sch. of Sao Carlos, Sao Paulo Univ.
Abstract :
The induction motors are largely used in several industry sectors. The dimensioning of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this paper is to use artificial neural networks as a tool for estimating the load torque applied to the induction motor shaft rather than conventional methods, which use classical identification techniques and mechanical load modeling. Simulation results are also presented to validate the proposed approach
Keywords :
induction motors; neural nets; power engineering computing; production engineering computing; torque; artificial neural networks; identification techniques; induction motors; industrial environment; load torque estimation; mechanical load modeling; Artificial neural networks; Differential equations; Electrical equipment industry; Induction motors; Industrial control; Neural networks; Shafts; State estimation; Steady-state; Torque measurement;
Conference_Titel :
Industrial Electronics and Applications, 2006 1ST IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
0-7803-9513-1
Electronic_ISBN :
0-7803-9514-X
DOI :
10.1109/ICIEA.2006.257362