한국펄프종이공학회:학술대회논문집 (Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference)
- 한국펄프종이공학회 2004년도 춘계학술발표논문집
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- Pages.86-96
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- 2004
Neural network을 이용한 OPR예측과 short circulation 동특성 분석
Dynamic analysis of short circulation with OPR prediction used neural network
- 발행 : 2004.04.08
초록
Identification of dynamics of short circulation during grade change operations in paper mills is very important for the effective plant operation. In the present study a prediction method of One Pass Retention(OPR) is proposed based on the neural network. The present method is used to analyze the dynamics of short circulation during grade change. Properties of the product paper largely depend upon the change in the OPR. In the present study the OPR is predicted from the training of the network by using grade change operation data. The results of the prediction are applied to the modeling equation to give flow rates and consistencies of short circulation.