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화학공정 모델을 이용한 데이터 보정 및 gross error의 감지
Data Reconcilation and Gross Error Detection Using Chemical Process Models
HWAHAK KONGHAK, October 1999, 37(5), 663-669(7), NONE
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Abstract
본 연구에서는 화학공정 측정값들에 대한 데이터 보정 및 gross error 감지를 위한 통합 시스템을 제안하였다. 제안된 시스템은 기본적인 단위 공정 모델 및 물성치 루틴을 갖추고 있어 하나의 독립된 시스템으로 사용이 가능하다. 제안된 데이터 보정 알고리듬은 비선형 방정식계로 표현되는 화학공정의 특성에 적합하도록 구현되었다. 이 방법은 선현 근사로 얻어진 제약식에 대해 반복적으로 계산을 수행하며, 방정식 중심법을 채택하여 계산의 효율성을 높이도록 구성되었다. 또한, gross error 감지를 위해 기존의 측정치 테스트를 개선한 교차점 테스트를 제안하고 사례 연구를 통해 이의 성능을 확인하였다.
In this paper an intergrated system for data reconcilation and gross error detection of the measurements in chemical processes is suggested. With unit process models and physical property routines, the proposed system itself works as an independent system. The proposed algorithm of data reconcilation is appropriate for the chemical processes that are consisted of the set of nonlinear equations. Since this method takes advantage of the repeated calculations of the constraint equations acquired by linear approximation, it improves the overall efficiency of the calculation. Also, the Point of the constraint equations better than the Measurements Test in co-linearity, for gross error detection is also suggested. The performance of the proposal system has been tested through a case study.
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