Data Processing and Reconciliation for Chemical Process Operations
eBook - PDF

Data Processing and Reconciliation for Chemical Process Operations

  1. 270 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Data Processing and Reconciliation for Chemical Process Operations

About this book

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. - 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

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Yes, you can access Data Processing and Reconciliation for Chemical Process Operations by José A. Romagnoli,Mabel Cristina Sanchez in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Chemical & Biochemical Engineering. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. CONTENTS
  3. PREFACE
  4. ACKNOWLEDGMENTS
  5. Chapter 1. General Introduction
  6. Chapter 2. Estimability and Redundancy within the Framework of the General Estimation Theory
  7. Chapter 3. Classification of the Process Variables for Chemical Plants
  8. Chapter 4. Decomposition Using Orthogonal Transformations
  9. Chapter 5. Steady-State Data Reconciliation
  10. Chapter 6. Sequential Processing of Information
  11. Chapter 7. Treatment of Gross Errors
  12. Chapter 8. Rectification of Process Measurement Data in Dynamic Situations
  13. Chapter 9. Joint Parameter Estimation–Data Reconciliation
  14. Chapter 10. Estimation of Measurement Error Variances from Process Data
  15. Chapter 11. New Trends
  16. Chapter 12. Case Studies
  17. APPENDIX. STATISTICAL CONCEPTS
  18. Index