Neural grey box model for power estimation in semiautogenous mill

  • Authors:
  • Tito Valenzuela;Karina Carvajal;Gonzalo Acuña;Max Chacón;Luis Magne

  • Affiliations:
  • Departamento de Ingeniería Informática, Facultad de Ingeniería, Universidad de Santiago de Chile,USACH, Santiago, Chile;Departamento de Ingeniería Informática, Facultad de Ingeniería, Universidad de Santiago de Chile,USACH, Santiago, Chile;Departamento de Ingeniería Informática, Facultad de Ingeniería, Universidad de Santiago de Chile,USACH, Santiago, Chile;Departamento de Ingeniería Informática, Facultad de Ingeniería, Universidad de Santiago de Chile,USACH, Santiago, Chile;Departamento de Ingeniería Metalúrgica, Facultad de Ingeniería, Universidad de Santiago de Chile, USACH, Santiago, Chile

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
  • Year:
  • 2005

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Abstract

Technology advances in semiautogenous milling have not been accompanied by advances in the operation of these mills, mainly in the estimates of load levels and the power of the mill. This article presents a grey box model that improves estimate of power. The obtained results are satisfactory and demonstrate that both the phenomenological model and the neural network strengthen each other, and the results are better than those obtained individually.