Performance Assessment for Process Monitoring and Fault Detection Methods (PDF)
(Sprache: Englisch)
The objective of Kai Zhang and his research is to assess the existing process monitoring and fault detection (PM-FD) methods. His aim is to provide suggestions and guidance for choosing appropriate PM-FD methods, because the performance assessment study for...
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The objective of Kai Zhang and his research is to assess the existing process monitoring and fault detection (PM-FD) methods. His aim is to provide suggestions and guidance for choosing appropriate PM-FD methods, because the performance assessment study for PM-FD methods has become an area of interest in both academics and industry. The author first compares basic FD statistics, and then assesses different PM-FD methods to monitor the key performance indicators of static processes, steady-state dynamic processes and general dynamic processes including transient states. He validates the theoretical developments using both benchmark and real industrial processes.
Contents
- Assessing the performance of T2 and Q fault detection statistics
- Proposing a new performance evaluation index called expected detection delay (EDD)
- Assessing the performance of different PM-FD methods using EDD when applied to detectingdifferent types of faults
- Assessing the state-space-based PM-FD methods when applied to a real hot strip mill process
Target Groups
- Scientists and students in the field of process control and statistical quality control
- Electrical engineers, chemical engineers, hot strip steel mill engineers
About the Author
Kai Zhang has just finished his PhD defense. His research area covers multivariate statistical process monitoring (PM) methods, data-driven fault detection (FD) methods and performance evaluation for PM-FD methods.
Autoren-Porträt von Kai Zhang
Kai Zhang has just finished his PhD defense. His research area covers multivariate statistical process monitoring (PM) methods, data-driven fault detection (FD) methods and performance evaluation for PM-FD methods.
Bibliographische Angaben
- Autor: Kai Zhang
- 2016, 1st ed. 2016, 153 Seiten, Englisch
- Verlag: Gabler, Betriebswirt.-Vlg
- ISBN-10: 3658159715
- ISBN-13: 9783658159719
- Erscheinungsdatum: 04.10.2016
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 2.69 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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