Model-based fault diagnosis in technical processes
- 1 March 2000
- journal article
- research article
- Published by SAGE Publications in Transactions of the Institute of Measurement and Control
- Vol. 22 (1), 57-101
- https://doi.org/10.1177/014233120002200104
Abstract
In this paper the state-of-the-art developments model-based fault diagnosis in technical processes are reviewed. Attention is focused upon both the analytical approaches that make use of the quantitative models and the knowledge-based approaches using qualitative models. Basic concepts and the advantages as well as disadvantages of different model-based fault diagnosis schemes are outlined.Keywords
This publication has 51 references indexed in Scilit:
- Integrated control, diagnosis and reconfiguration of a heat exchangerIEEE Control Systems, 1998
- Deterministic nonlinear observer-based approaches to fault diagnosis: A surveyControl Engineering Practice, 1997
- An overview of fuzzy modeling for controlControl Engineering Practice, 1996
- A bilinear fault detection observer and its application to a hydraulic drive systemInternational Journal of Control, 1996
- Residual generation and fault detection for discrete-time systems using an l∞ techniqueInternational Journal of Control, 1996
- Fuzzy systems design based on a hybrid neural structure and application to the fault diagnosis of technical processesControl Engineering Practice, 1996
- Design of unknown input observers and robust fault detection filtersInternational Journal of Control, 1996
- Fault detection and isolation observersInternational Journal of Control, 1994
- Enhancement of robustness in observer-based fault detection†International Journal of Control, 1994
- Representing and diagnosing dynamic process data using neural networksEngineering Applications of Artificial Intelligence, 1992