Data reconciliation & gross error detection an intelligent use of process data

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 prob...

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Bibliographic Details
Main Author: Narasimhan, Shankar.
Other Authors: Jordache, Cornelius.
Format: eBook
Language: English
Published: Houston : Gulf Pub. Co., ©2000.
Subjects:
Chemical process control > Automation.
Automatic data collection systems.
Error analysis (Mathematics)
elektronické knihy
electronic books
ISBN: 9780884152552
9780080503714
9781615836574
Physical Description: 1 online zdroj (xvii, 406 pages) : illustrations

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Table of contents

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100 1 |a Narasimhan, Shankar. 
245 1 0 |a Data reconciliation & gross error detection  |h [elektronický zdroj] :  |b an intelligent use of process data /  |c Shankar Narasimhan and Cornelius Jordache. 
246 3 |a Data reconciliation and gross error detection 
260 |a Houston :  |b Gulf Pub. Co.,  |c ©2000. 
300 |a 1 online zdroj (xvii, 406 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
520 |a 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. 
505 0 |a : Introduction. Measurement Errors and Error Reduction Techniques. Steady State Data Reconciliation for Bilinear Systems. Nonlinear Steady State Data Reconciliation. Data Reconciliation in Dynamic Systems. Introduction to Gross Error Detection. Multiple Gross Error Identification Strategies for Steady State Processes. Gross Error Detection in Dynamic Processes. Design of Sensor Networks. Industrial Applications of Data Reconciliation and Gross Error Detection Technologies. Appendix A: Basic concepts of linear algebra. Appendix B: Basic concepts of Graph Theory. Appendix C: Statistical Hypotheses Testing. 
504 |a Includes bibliographical references and indexes. 
590 |a Knovel Library  |b ACADEMIC - Process Design, Control & Automation 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty univerzity 
650 0 |a Chemical process control  |x Automation. 
650 0 |a Automatic data collection systems. 
650 0 |a Error analysis (Mathematics) 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Jordache, Cornelius. 
776 0 8 |i Print version:  |a Narasimhan, Shankar.  |t Data reconciliation & gross error detection.  |d Houston : Gulf Pub. Co., ©2000  |z 0884152553  |z 9780884152552  |w (DLC) 99044868  |w (OCoLC)42080372 
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992 |a BK  |c KNOVEL 
999 |c 82788  |d 82788 
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