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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| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Houston :
Gulf Pub. Co.,
©2000.
|
| Subjects: | |
| ISBN: | 9780884152552 0884152553 9780080503714 0080503713 9781615836574 1615836578 1281035203 9781281035202 9786611035204 6611035206 |
| Physical Description: | 1 online resource (xvii, 406 pages) : illustrations |
Cover
Table of contents
| LEADER | 04366cam a2200505 a 4500 | ||
|---|---|---|---|
| 001 | kn-ocn162594415 | ||
| 003 | OCoLC | ||
| 005 | 20240717213016.0 | ||
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| 008 | 070806s2000 txua ob 001 0 eng d | ||
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| 020 | |a 9780884152552 | ||
| 020 | |a 0884152553 | ||
| 020 | |a 9780080503714 |q (electronic bk.) | ||
| 020 | |a 0080503713 |q (electronic bk.) | ||
| 020 | |a 9781615836574 |q (electronic bk.) | ||
| 020 | |a 1615836578 |q (electronic bk.) | ||
| 020 | |a 1281035203 | ||
| 020 | |a 9781281035202 | ||
| 020 | |a 9786611035204 | ||
| 020 | |a 6611035206 | ||
| 035 | |a (OCoLC)162594415 |z (OCoLC)173807670 |z (OCoLC)179796647 |z (OCoLC)352550989 |z (OCoLC)607443306 |z (OCoLC)647654016 |z (OCoLC)658055994 |z (OCoLC)671235929 |z (OCoLC)977609583 |z (OCoLC)1032364753 |z (OCoLC)1032603494 |z (OCoLC)1035697400 |z (OCoLC)1058659318 |z (OCoLC)1086524816 |z (OCoLC)1159604497 | ||
| 042 | |a dlr | ||
| 100 | 1 | |a Narasimhan, Shankar. | |
| 245 | 1 | 0 | |a Data reconciliation & gross error detection : |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 resource (xvii, 406 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty | ||
| 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 |b Knovel (All titles) | ||
| 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 |
| 856 | 4 | 0 | |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpDRGEDAIF/data-reconciliation-gross?kpromoter=marc |y Full text |
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