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.
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