조명전기설비학회논문지 (Journal of the Korean Institute of Illuminating and Electrical Installation Engineers)

한국조명전기설비학회 (The Korean Institute of IIIuminating and Electrical Installation Engineers)
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신경망을 이용한 판온예측모델내 공정상수 설정 방법

A Computing Method of a Process Coefficient in Prediction Model of Plate Temperature using Neural Network

  • 김태은 (태창기계공업 기업부설연구소) ;
  • 이해영 (영남대학교 전기공학과)
  • 투고 : 2014.07.30
  • 심사 : 2014.09.30
  • 발행 : 2014.11.28
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초록

This paper presents an algorithmic type computing technique of process coefficient in predicting model of temperature for reheating furnace and also suggests a design method of neural network model to find an adequate value of process coefficient for arbitrary operating conditions including test conditons. The proposed neural network use furnace temperature, line speed and slab information as input variables, and process coefficient is output variable. Reasonable process coefficients can be obtained by an algorithmic procedure proposed in this paper using process data gathered at test conditons. Also, neural network model output equal process coefficient under same input conditions. This means that adquate process coefficients can be found by only computing neural network model without additive test even if operating conditions vary.

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참고문헌

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