Fault Detection, Supervision and Safety for Technical Processes: Safeprocess'94 - IFAC Symposium, Helsinki University of Technology, Espoo, Finland, 13-16 June 1994

Fault detection, supervision and safety are an essential part of modern control engineering. In this publication, over 200 experts from various fields and application areas present their latest results on reliability, availability and safety of technical processes, covering both theoretical and practical problems. Applications in all phases are covered, from design, start-up, operation, maintenance through to repair. Relevant methods and tools for monitoring, diagnosis and detection are discussed as well as the increasingly important topics of failure data collection and analysis, human factors and man-machine interfaces. This volume lays strong emphasis on applications and aims to promote further research and industrial co-operation.

Table of Contents:
Part 1 Plenary paper: robust model-based fault diagnosis - the state of the art, R.J. Patton. Part 2 Model-based diagnosis I: a new fault diagnosis approach in stochastic linear systems, J.Y. Keller et al. Part 3 Model-based diagnosis II: simultaneous detection, location and identification of faults for dynamic systems, G. Bloch et al. Part 4 Model-based diagnosis III: continuous and discrete time identification for fault detection, Sprosser and G.L. Gissinger. Part 5 Applications - power plants I: statistical diagnostics - a new integrating tool for man-machine interfaces, E.A. Averbukh et al. Part 6 Applications - power plants II: long-term wear monitoring and wear prediction by means of wear models, P. Neuenschwander et al. Part 7 Applications - chemical plants: fault detection of large parameter changes in a wastewater plant, M.J. Fuente et al. Part 8 Reliability and safety analysis I: communicating the safety aspects of industrial plants, K. Kaarela and J. Oksanen. Part 9 Reliability and safety analysis II: developments in reliability data collection and analysis, J.K. Vaurio. Part 10 Robust methods: robust fault detection and isolation in nonlinear systems, A. Zhirabok and O. Preobrazhenska. Part 11 Plenary paper: safety of nuclear power - who learns from whom?, B. Wahlstrom et al. Part 12 Model based diagnosis IV: holistic modelling as a tool for the diagnosis of critical complex systems, H.G. Natke and C. Cempel. Part 13 Model based diagnosis V: fault detection for sequentially controlled machines using temporal constraint nets, M. Minas. Part 14 Fuzzy and knowledge based methods: causal graphs for model-based diagnosis, J. Montmain and L. Leyval. Part 15 Applications - combustion engines: fuzzy classification of internal combustion engine faults based on neural network, Hua Deng et al. Part 16 Special case paper: model-based diagnosis of automotive engines - case study on a physical vehicle, J. Gertler and M. Costin. Part 17 Applications - components I: a low cost tool for diagnosis of antifriction bearings, A. Seeliger et al. Part 18 Applications - components II: sensor fault detection and isolation on a pilot heat exchanger, X. Simonart and M. Kinnaert. Part 19 Benchmark: diesel engine actuator fault isolation using multiple models hypothesis tests, S.B. Nielsen. Part 20 Special case paper: application of fuzzy logic to process supervision and fault diagnosis, P.M. Frank. Part 21 Comparison of diagnosis methods: detection of addictive and multiplicative faults - parity space vs. parameter estimation, Hofling and Pfeufer. Part 22 Case - inverted pendulum: fault detection and isolation in mechanical systems using adaptive friction compensation, D. Sauter et al. Part 23 Plenary paper: integration of fault detection and diagnosis methods, R. Isermann. Part 24 Neural networks: using neural networks in nuclear power plants for state diagnosis, J.P. Bonfert. Part contents).