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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/75966
Title: 
Speed estimation for induction motor using neural networks method
Author(s): 
Institution: 
  • UTFPRCP
  • Universidade de São Paulo (USP)
  • Universidade Estadual Paulista (UNESP)
  • Universidade Federal do ABC (UFABC)
ISSN: 
1548-0992
Abstract: 
This work presents an alternative approach based on neural network method in order to estimate speed of induction motors, using the measurement of primary variables such as voltage and current. Induction motors are very common in many sectors of the industry and assume an important role in the national energy policy. The nowadays methodologies, which are used in diagnosis, condition monitoring and dimensioning of these motors, are based on measure of the speed variable. However, the direct measure of this variable compromises the system control and starting circuit of an electric machinery, reducing its robustness and increasing the implementation costs. Simulation results and experimental data are presented to validate the proposed approach. © 2003-2012 IEEE.
Issue Date: 
15-Jul-2013
Citation: 
IEEE Latin America Transactions, v. 11, n. 2, p. 768-778, 2013.
Time Duration: 
768-778
Keywords: 
  • artificial neural networks
  • speed estimator
  • Three-phase induction motors
  • Alternative approach
  • Experimental datum
  • Implementation cost
  • National energy policy
  • Neural network method
  • Speed estimation
  • Speed estimator
  • Three phase induction motor
  • Condition monitoring
  • Electric machinery
  • Energy policy
  • Machinery
  • Neural networks
  • Starting
  • Induction motors
Source: 
http://dx.doi.org/10.1109/TLA.2013.6533966
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/75966
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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