Authors:
- Covers a variety of data-driven process monitoring techniques
- Includes detailed applications in chemical plant simulation
- Includes homework problems to enable deeper comprehension of the text
Part of the book series: Advances in Industrial Control (AIC)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (11 chapters)
-
Front Matter
-
Introduction
-
Front Matter
-
-
Background
-
Front Matter
-
-
Application
-
Front Matter
-
-
Other Approaches
-
Front Matter
-
-
Back Matter
About this book
The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques.
The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.
Authors and Affiliations
-
Exxon Production Research Company, Houston, USA
Evan L. Russell
-
Department of Chemical Engineering, University of Illinois at Urbana-Champaign, Urbana, USA
Leo H. Chiang, Richard D. Braatz
Bibliographic Information
Book Title: Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
Authors: Evan L. Russell, Leo H. Chiang, Richard D. Braatz
Series Title: Advances in Industrial Control
DOI: https://doi.org/10.1007/978-1-4471-0409-4
Publisher: Springer London
-
eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag London 2000
Softcover ISBN: 978-1-4471-1133-7Published: 01 November 2012
eBook ISBN: 978-1-4471-0409-4Published: 06 December 2012
Series ISSN: 1430-9491
Series E-ISSN: 2193-1577
Edition Number: 1
Number of Pages: XIII, 192
Number of Illustrations: 41 b/w illustrations
Topics: Industrial Chemistry/Chemical Engineering, Database Management, Data Structures, Control, Robotics, Mechatronics