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.
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| Main Authors | , |
|---|---|
| Format | eBook Book |
| Language | English |
| Published |
San Diego, Calif. ; Tokyo
Academic Press
2000
Elsevier Science & Technology |
| Edition | 1 |
| Series | Process systems engineering |
| Subjects | |
| Online Access | Get full text |
| ISBN | 0125944608 9780125944601 |
Cover
Table of Contents:
- 7.2. Gross Error Detection -- 7.3. Identification of the Measurements with Gross Error -- 7.4. Estimation of the Magnitude of Bias and Leaks -- 7.5. A Recursive Scheme for Gross Error Identification and Estimation -- 7.6. Conclusions -- Notation -- References -- Appendix A -- Appendix B -- Chapter 8. Rectification of Process Measurement Data in Dynamic Situations -- 8.1. Introduction -- 8.2. Dynamic Data Reconciliation: A Filtering Approach -- 8.3. Dynamic Data Reconciliation: Using Nonlinear Programming Techniques -- 8.4. Conclusions -- Notation -- References -- Chapter 9. Joint Parameter Estimation-Data Reconciliation -- 9.1. Introduction -- 9.2. The Parameter Estimation Problem -- 9.3. Joint Parameter Estimation-Data Reconciliation Problem -- 9.4. Dynamic Joint State-Parameter Estimation: A Filtering Approach -- 9.5. Dynamic Joint State-Parameter Estimation: A Nonlinear Programming Approach -- 9.6. Conclusions -- Notation -- References -- Chapter 10. Estimation of Measurement Error Variances from Process Data -- 10.1. Introduction -- 10.2. Direct Method -- 10.3. Indirect Method -- 10.4. Robust Covariance Estimator -- 10.5. Conclusions -- Notation -- References -- Appendix A -- Chapter 11. New Trends -- 11.1. Introduction -- 11.2. The Bayesian Approach -- 11.3. Robust Estimation Approaches -- 11.4. Principal Component Analysis in Data Reconciliation -- 11.5 Conclusions -- Notation -- References -- Chapter 12. Case Studies -- 12.1. Introduction -- 12.2. Decomposition/Reconciliation in a Section of an Olefin Plant -- 12.3. Data Reconciliation of a Pyrolysis Reactor -- 12.4. Data Reconciliation of an Experimental Distillation Column -- 12.5. Conclusions -- Notation -- References -- APPENDIX. STATISTICAL CONCEPTS -- 1. Frequency Distributions -- 2 Measures of Central Tendency and Spread -- 3. Estimation -- 4. Confidence Intervals
- Cover -- CONTENTS -- PREFACE -- ACKNOWLEDGMENTS -- Chapter 1. General Introduction -- 1.1. Reliable and Complete Process Knowledge -- 1.2. Some Issues Associated with a General Data Reconciliation Problem -- 1.3. About This Book -- References -- Chapter 2. Estimability and Redundancy within the Framework of the General Estimation Theory -- 2.1. Introduction -- 2.2. Basic Concepts and Definitions -- 2.3. Decomposition of the General Estimation Problem -- 2.4. Structural Analysis -- 2.5. Conclusions -- Notation -- References -- Appendix A -- Chapter 3. Classification of the Process Variables for Chemical Plants -- 3.1. Introduction -- 3.2. Modeling Aspects -- 3.3. Classification of Process Variables -- 3.4. Analysis of the Process Topology -- 3.5. Different Approaches for Solving the Classification Problem -- 3.6. Use of Output Set Assignments for Variable Classification -- 3.7. The Solution of Special Problems -- 3.8. A Complete Classification Example -- 3.9. Formulation of a Reduced Reconciliation Problem -- 3.10. Conclusions -- Notation -- References -- Appendix A -- Appendix B -- Chapter 4. Decomposition Using Orthogonal Transformations -- 4.1. Introduction -- 4.2. Linear Mass Balances -- 4.3. Bilinear Multicomponent and Energy Balances -- 4.4. Conclusions -- Notation -- References -- Chapter 5. Steady-State Data Reconciliation -- 5.1. Introduction -- 5.2. Problem Formulation -- 5.3. Linear Data Reconciliation -- 5.4. Nonlinear Data Reconciliation -- 5.5. Conclusions -- Notation -- References -- Appendix A -- Chapter 6. Sequential Processing of Information -- 6.1. Introduction -- 6.2. Sequential Processing of Constraints -- 6.3. Sequential Processing of Measurements -- 6.4. Alternative Formulation from Estimation Theory -- 6.5. Conclusions -- Notation -- References -- Appendix A -- Chapter 7. Treatment of Gross Errors -- 7.1. Introduction
- 5. Testing of Statistical Hypotheses -- References -- Index