Data Reconciliation and Gross Error Detection. An Intelligent Use of Process Data

Data Reconciliation and Gross Error Detection. An Intelligent Use of Process Data By Shankar Narasimhan and Cornelius Jordache (Auth.)
2000 | 411 Pages | ISBN: 0884152553 | PDF | 6 MB
This is an excellent book on the subject – the authors have covered all the bases. If you want a book on data reconciliation and gross error detection, this is as complete and thorough a book as I can imagine. – Les A. Kane, Editor, Advanced Process Control and Information Systems Content: Acknowledgments, Pages xiii-xivPreface, Pages xv-xvii1 – The Importance of Data Reconciliation and Gross Error Detection, Pages 1-312 – Measurement Errors and Error Reduction Techniques, Pages 32-583 – Linear Steady-State Data Reconciliation, Pages 59-844 – Steady-State Data Reconciliation for Bilinear Systems, Pages 85-1185 – Nonlinear Steady-State Data Reconciliation, Pages 119-1416 – Data Reconciliation in Dynamic Systems, Pages 142-1737 – Introduction to Gross Error Detection, Pages 174-2258 – Multiple Gross Error Identification Strategies for Steady-State Processes, Pages 226-2809 – Gross Error Detection in Linear Dynamic Systems, Pages 281-29910 – Design of Sensor Networks, Pages 300-32611 – Industrial Applications of Data Reconciliation and Gross Error Detection Technologies, Pages 327-372Appendix A – Basic Concepts in Linear Algebra, Pages 373-377Appendix B – Graph Theory Fundamentals, Pages 378-383Appendix C – Fundamentals of Probability and Statistics, Pages 384-393Index, Pages 394-402Author Index, Pages 403-405The Authors, Page 406