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2011 | OriginalPaper | Chapter

6. Fault Diagnosis

Authors : Prof. Fabrizio Caccavale, Mario Iamarino, Francesco Pierri, Vincenzo Tufano

Published in: Control and Monitoring of Chemical Batch Reactors

Publisher: Springer London

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Abstract

This chapter is focused on model-based fault diagnosis for chemical batch reactors. First, the basic principles of model-based fault diagnosis are briefly overviewed. Then, a general approach to fault diagnosis for chemical batch reactors, based on nonlinear adaptive observers, is presented. The proposed approach combines both the physical redundancy and analytical redundancy concepts to design an effective diagnosis scheme. Namely, redundant temperature sensors are considered both in the jacket and in the reactor vessel; then, sensor measurements are processed so as to recognize the faulty sensor and output a healthy measure. The healthy measure is used to feed a bank of observers, in such a way to perform detection, isolation, and identification of process and actuator faults. The main properties of the diagnosis algorithms (convergence, isolability, and detectability) are rigorously analyzed. Finally, a case study, based to the phenol–formaldehyde reaction introduced in Chap. 2, is developed.

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Metadata
Title
Fault Diagnosis
Authors
Prof. Fabrizio Caccavale
Mario Iamarino
Francesco Pierri
Vincenzo Tufano
Copyright Year
2011
Publisher
Springer London
Book
Control and Monitoring of Chemical Batch Reactors

Print ISBN: 978-0-85729-194-3

Electronic ISBN: 978-0-85729-195-0

Copyright Year: 2011

DOI
https://doi.org/10.1007/978-0-85729-195-0_6