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Open AccessJournal Article

Detecting errors in process data

W. A. Heenan, +1 more
- 01 Jan 1986 - 
- Vol. 93, Iss: 21, pp 99-103
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TLDR
In this article, a description of plusieurs methodes de detection des erreurs, que l'on applique au calcul des bilans matiere dans un reseau de distribution de vapeur
Abstract
Description de plusieurs methodes de detection des erreurs, que l'on applique au calcul des bilans matiere dans un reseau de distribution de vapeur

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Steady-state data reconciliation for absorption refrigeration systems

TL;DR: In this paper data reconciliation is applied to the steady-state operational data of a single-effect ammonia/water absorption chiller to identify and eliminate the sources of gross errors, and to obtain performance calculations that are in agreement with the laws of conservation.
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A new approach for improved identification of measurement bias

TL;DR: In this paper, the authors present a technique that can completely and accurately identify measurement bias in cases where it is not possible to use the method of Rollins and Davis (1992, 1993) and where Narasimhan and Mah (1987) fail to perform accurately.

A knowledge-based system architecture for diagnosis and sensor validation in chemical process plants

TL;DR: A knowledge-based system architecture for malfunction diagnosis and sensor validation in chemical process plants is discussed and a novel sensor validation strategy is developed that streamlines the validation by leveraging functional and operational knowledge about the sensors.