Abstract
This paper deals with the use of neuro-fuzzy approach to fault detection in industrial processes. The general information regarding the model based fault detection and neuro-fuzzy techniques is presented. The neuro-fuzzy simulator is employed to fault detection in the boiler drum. To illustrate our approach, the simulation results are presented in the final part of the paper.
Keywords
- Fault Detection
- Control System Technology
- Artificial Intelligence Method
- Steam Power Plant
- Fault Detection Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Bauman, E., Dorofeyuk, A., Filev, D.: Fuzzy identification of non-linear dynamical systems. Proceedings International Conference on Fuzzy Logic and Neural Nets, Iizuka, Japan (1990) 1013–1015
Korbicz, J., Pieczynski, A.: Dynamic model of steam power plant. Report of Department of Robotics and Software Engineering, Zielona Gora, Poland (1993) (in Polish)
Maki, Y., Loparo, K.A.: A neural network approach to fault detection and diagnosis in industrial processes. IEEE Trans. on Control Systems Technology, Vol. 5, No. 6 (1997) 529–541
Marcu, T., Mirea, L.: Robust detection and isolation of process faults using neural networks. IEEE Trans. on Control Systems Technology, Vol. 10 (1997) 72–79
Yager, R.R., Filev, D.P.: Essentials of fuzzy modelling and control. John Wiley and Sons, Inc. (1994)
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© 2000 Springer-Verlag Berlin Heidelberg
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Kowal, M., Korbicz, J. (2000). Neuro-Fuzzy Detector for Industrial Process. In: Hampel, R., Wagenknecht, M., Chaker, N. (eds) Fuzzy Control. Advances in Soft Computing, vol 6. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1841-3_26
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DOI: https://doi.org/10.1007/978-3-7908-1841-3_26
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1327-2
Online ISBN: 978-3-7908-1841-3
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