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

Mostrar otras versiones (1)

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...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Narasimhan, Shankar
Otros Autores: Jordache, Cornelius
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Houston : Gulf Pub. Co., ©2000.
Temas:
Chemical process control > Automation.
Automatic data collection systems.
Error analysis (Mathematics)
Procédés chimiques > Contrôle > Automatisation.
Collecte automatique des données.
Théorie des erreurs.
TECHNOLOGY & ENGINEERING > Chemical & Biochemical.
SCIENCE > Chemistry > Industrial & Technical.
Ausreißerwert
Datenerhebung
Prozessüberwachung
Acceso en línea:Texto completo
Tabla de Contenidos:
  • : 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.

Ejemplares similares