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Data Reconciliation and Gross Error Detection: An Intelligent Use of Process Data
Data Reconciliation and Gross Error Detection: An Intelligent Use of Process Data
Date: 27 April 2011, 11:20

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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 corrupted by power supply fluctuations, network transmission and signal 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.

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