Neural approach for induction motor load torque identification in industrial applications

Autor(es)

Goedtel, Alessandro ; da Silva, Ivan N. ; Serni, Paulo J. A. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: PROCEEDINGS OF THE 2007 IEEE CONFERENCE ON CONTROL APPLICATIONS, VOLS 1-3; v. N/A, p. 2-pg., 2007-01-01.

Resumo

Induction motors are widely used in several industrial sectors. However, the dimensioning of induction motors is often inaccurate because, in most cases, the load behavior in the shaft is completely unknown. The proposal of this paper is to use artificial neural networks as a tool for dimensioning induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since the proposed approach uses current, voltage and speed values as the only input parameters, one of its potentialities is related to the facility of hardware implementation for industrial environments and field applications. Simulation results are also presented to validate the proposed approach. (AU)

• Processo FAPESP: 06/56093-3 - Dinamotor - sistema de dimensionamento inteligente automatico de motor de inducao atraves de tecnicas sensorless.
• Beneficiário: Ivan Nunes da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Regular