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Data processing and reconciliation for chemical process operations /

Computer techniques have made online measurements available at every sampling period in a chemical process. However, measurement errors are introduced that require suitable techniques for data reconciliation and improvements in accuracy. Reconciliation of process data and reliable monitoring are ess...

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Bibliographic Details
Main Authors: Romagnoli, Jose A. Jose Alberto
Corporate Authors: Elsevier Science & Technology
Group Author: Sa nchez, Mabel Cristina
Published: Academic Press,
Publisher Address: San Diego :
Publication Dates: 2000.
Literature type: eBook
Language: English
Series: Process systems engineering ; v. 2
Subjects:
Chemical process control > Automation
Automatic data collection systems
Error analysis Mathematics
Chemical processes
Chemical process control
Proce de s chimiques > Contro le > Automatisation
Collecte automatique des donne es
Erreurs, The orie des
TECHNOLOGY & ENGINEERING > Chemical & Biochemical
SCIENCE > Chemistry > Industrial & Technical
Electronic books
Online Access: http://www.sciencedirect.com/science/bookseries/18745970/2
Summary: Computer techniques have made online measurements available at every sampling period in a chemical process. However, measurement errors are introduced that require suitable techniques for data reconciliation and improvements in accuracy. Reconciliation of process data and reliable monitoring are essential to decisions about possible system modifications (optimization and control procedures), analysis of equipment performance, design of the monitoring system itself, and general management planning. While the reconciliation of the process data has been studied for more than 20 years, there is
Carrier Form: 1 online resource (xv, 270 pages) : illustrations.
Bibliography: Includes bibliographical references and indexes.
ISBN: 9780080530277
0080530273
1281049867
9781281049865
Index Number: TP155
CLC: TQ02-37
Contents: General Introduction. Reliable and Complete Knowledge. Some Issues Associated with a General Data Reconciliation Problem. About This Book. References of Chapter 1. Estimability and Redundancy Within the Framework of the General Estimation Theory. Introduction. Basic Concepts and Definitions. Decomposition of the General Estimation Problem. Structural Analysis. Conclusions. Notation. References of Chapter 2. Appendix 2 -- A. Classification of the Process Variables for Chemical Plants. Introduction. Modeling Aspects. Classification of Process Variables. Analysis of the Process Topology. Differ

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