Performance Assessment for Process Monitoring and Fault Detection Methods

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.

List of 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 detecting different types of faults.- Assessing the state-space-based PM-FD methods when applied to a real hot strip mill process.

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.

Summary

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.

Product details

• Authors: Kai Zhang
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2016
• EAN: 9783658159702
• ISBN: 978-3-658-15970-2
• No. of pages: 153
• Dimensions: 165 mm x 11 mm x 212 mm
• Weight: 237 g
• Illustrations: XXI, 153 p. 55 illus.
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; C, computer science, Control and Systems Theory, Chemical Engineering, Industrial Chemistry, Systems Theory, Control, Mathematical & statistical software, Mathematical statistics, Probability and Statistics in Computer Science, Control engineering, Industrial chemistry & chemical engineering, Automatic control engineering, System Theory, Cybernetics & systems theory, Industrial Chemistry/Chemical Engineering, Cybernetics and systems theory