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Optimization of Vertical Roller Mill by Using Artificial Neural Networks

신경회로망을 이용한 수직형 롤러 분쇄기의 최적설계

  • 이동우 (동아대학교 기계공학과) ;
  • 조석수 (강원대학교 자동차공학과)
  • Received : 2009.10.14
  • Accepted : 2010.04.26
  • Published : 2010.07.01

Abstract

The vertical roller mill is important for machine grinding and mixing various crude materials in the process of producing Portland cement. A vertical roller mill is subjected to cyclic bending stress because of the roller load. Because of the cyclic bending stress, only $4{\times}10^6-8{\times}10^6$ cycles are achieved instead of $4{\times}10^7$ cycles. The stress also causes fractures at the edge of grinding path of the outer roller. The expenses incurred in repairing the grinding path amounts to 30% of the total maintenance cost. Therefore, it is desirable to redesign the vertical roller mill in order to reduce the expenses incurred in repairing the roller. In this study, artificial neural networks (ANNs) were applied in order to solve the multiobjective optimization problem for vertical roller mills by using the function approximation ability of ANNs. To learn and generalize ANNs, the maximum and minimum stresses were estimated from the results of the finite-element analysis of a vertical roller mill. Thus, ANNs could be applied to solve the multiobjective optimization problem.

Keywords

Vertical Roller Mill;Neural Networks;Optimization

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