신경망을 이용한 열간 압연하중 예측용 탄소당량식의 개발

Determination of Carbon Equivalent Equation by Using Neural Network for Roll Force Prediction in hot Strip Mill

  • 김필호 (포항산업과학연구원 압연설비 ENG. 연구팀) ;
  • 문영훈 (포항산업과학연구원 압연설비 ENG. 연구팀) ;
  • 이준정 (포항산업과학연구원 압연설비 ENG. 연구팀)
  • 발행 : 1997.12.01

초록

New carbon equivalent equation for the better prediction for the better prediction of roll force in a continuous hot strip mill has been formulated by applying a neural network method. In predicting roll force of steel strip, carbon equivalent equation which normalize the effects of various alloying elements by a carbon equivalent content is very critical for the accurate prediction of roll force. To overcome the complex relationships between alloying elements and operational variables such as temperature, strain, strain rate and so forth, a neural network method which is effective for multi-variable analysis was adopted in the present work as a tool to determine a proper carbon equivalent equation. The application of newly formulated carbon equivalent equation has increased prediction accuracy of roll force significantly and the effectiveness of neural network method is well confirmed in this study.

키워드

참고문헌

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