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Data Reconciliation and Gross Error Detection

Data Reconciliation and Gross Error Detection

Dr. Shankar Narasimhan, Ph.D. (Ch.E.) | Dr. Cornelius Jordache, Ph.D. (Ch.E)


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This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustively explained.
Data errors can cause big problems in any process plant or refinery. Process measurements can be correupted by power supply flucutations, network transmission and signla conversion noise, analog input filtering, changes in ambient conditions, instrument malfunctioning, miscalibration, and the wear and corrosion of sensors, among other factors. Here's a book that helps you detect, analyze, solve, and avoid the data acquisition problems that can rob plants of peak performance. This indispensable volume provides crucial insights into data reconciliation and gorss error detection techniques that are essential fro optimal process control and information systems.
This book is an invaluable tool for engineers and managers faced with the selection and implementation of data reconciliation software, or for those developing such software. For industrial personnel and students, Data Reconciliation and Gross Error Detection is the ultimate reference.
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