Engineering - Industrial, Data Processing, Computer Mathematics, General & Miscellaneous Chemical Engineering
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Overview
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 no single source providing a unified approach to the area with instructions on implementation. Data Processing and Reconciliation for Chemical Process Operations is that source. Competitiveness on the world market as well as increasingly stringent environmental and product safety regulations have increased the need for the chemical industry to introduce such fast and low cost improvements in process operations.Key Features
* Introduces the first unified approach to this important field
* Bridges theory and practice through numerous worked examples and industrial case studies
* Provides a highly readable account of all aspects of data classification and reconciliation
* Presents the reader with material, problems, and directions for further study
Audience: Industrial practitioners and academic researchers in chemical engineering (particularly in process monitoring and control), as well as advanced (senior) undergraduate and graduate students.
Editorials
Booknews
Discussing the main issues in the treatment and reconciliation of plant data, this text covers the concepts of estimability and redundancy in steady-state processes; process variable classification for linear and nonlinear plant models; the adjustment of measurements for different kinds of plant models; advantages of sequential processing of measurements and constraints; definition and analysis of the data reconciliation problem; analysis of dynamic and quasi-steady-state processes; the problem of joint parameter estimation-data reconciliation; and trends in the field. Case studies are presented in the final chapter. Suitable for graduate students, advanced undergraduates in chemical engineering, and practitioners engaged in the industrial application of reconciliation techniques. Annotation c. Book News, Inc., Portland, OR (booknews.com)Book Details
Published
October 25, 1999
Publisher
San Diego : Academic Press, c2000.
Pages
270
Format
Hardcover
ISBN
9780125944601