On-line fault detection and supervision in the chemical process industries : selected papers from the IFAC Symposium, Newark, Delaware, USA, 22-24 April 1992
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Bibliographic Information
On-line fault detection and supervision in the chemical process industries : selected papers from the IFAC Symposium, Newark, Delaware, USA, 22-24 April 1992
（IFAC symposia series, 1993,
Published for the International Federation of Automatic Control by Pergamon Press, 1993
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Papers from the IFAC Symposium on On-line Fault Detection and Supervision in the Chemical Process Industries
Includes bibliographical references and indexes
Description and Table of Contents
Description
The papers presented at this Symposium were grouped into five major sections: Strategies for the detection and diagnosis of process faults; Modeling, validation, and interpretation of process trends; Supervision and control of chemical plants; Neural networks in process supervision and fault diagnosis. Industrial applications in process supervision and fault diagnosis; The fifty-two papers in this volume cover both theoretical and practical/implementational aspects of systems in the process control industry.
Table of Contents
Section headings and selected papers: Strategies for the Detection and Diagnosis of Process Faults. Robust model-based fault detection in dynamic systems, P. M. Frank. Structured residuals for fault isolation, disturbance decoupling and modelling error robustness, J. Gertler. Facilitated operations using complete and rigorous models, P. K. Nair. Modeling, Validation and Interpretation of Process Trends. Model-based measurement validation using MFM, J. E. Larsson. A recursive detection scheme for serially correlated process data, R. J. Rowlands & M. Pereira-Leite. The implications of digital communications on sensor validation, M. Henry & G. Wood. Supervision and Control of Chemical Plants. On-line hydrogen resource management in a refinery using fuzzy optimization, T. F. Petti & P. S. Dhurjati. Novel method for the optimal control of batch processes, V. Pillai et al. Protection and perpetual supervision systems of oxygen turbocompressors, W. Prokop. Neural Networks in Process Supervision and Fault Diagnosis. Use of artificial neural networks to monitor faults and for troubleshooting in the process industries, D. M. Himmelblau. On the classification characteristics of networks with ellipsoidal activation functions: a comparative study, S. N. Kavuri & V. Venkatasubramanian. A decomposition approach to solving large-scale fault diagnosis problems with modular neural networks, J. A. Leonard & M. A. Kramer. Industrial Applications in Process Supervision and Fault Diagnosis. Beyond Falcon: industrial applications of knowledge-based systems, D. A. Rowan. On-line process monitoring, control and supervision for an industrial polymerization process, M. T. Vester. On line diagnosis of water chemistry in thermal power plant, N. V. L. Addanki & R. Sethuraman. Author index. Keyword index.
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