Abstract
A knowledge-based model for on-line diagnosis of complex dynamic systems is proposed. Domain knowledge is modelled via causal networks which consider temporal relationships among symptoms and causes. Inference and task knowledge is described using the Common-KADS methodology. The main feature of the proposal is that the diagnosis task is able to track the evolution of the system incorporating new symptoms to the diagnosis process. Diagnosis is conceived as a task to be carried out by a supervisory system, which could select the suitable causal network to perform diagnosis, depending on the current system configuration and operation point.
This work has been funded by grants CICyT TAP99-0344 and MCyT DPI2002-01809 from Spanish government.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Balakrishnan, K., Honavar, V.: Intelligent diagnosis systems. Journal of Intelligent Systems 8 (1998) 239–290
Cauvin, S., Cordier, M.O., Dousson, C., Laborie, P., Lévy, F., Montmain, J., Porcheron, M., Servet, I., Travé-Massuyès, L.: Monitoring and Alarm Interpretation in Industrial Environments. AI Communications 11 (1998) 139–173
Chen, J., Patton, R.: Robust model based fault diagnosis for dynamic systems. Kluwer Academic Publisher (1999)
Dressler, O., Struss, P.: The consistency based approach to automated diagnosis of devices. In: Principles of knowledge representation. CSLI publications, Stanford (1996) 269–314
Price, C.: Computer-based diagnostic systems. Springer (1999)
Acosta, G., Alonso, C., Pulido, B.: Basic Tasks for Knowledge Based Supervision in Process Control. Engineering Applications of Artificial Intelligence 14 (2002) 441–455
Guckenbiehl, T., Schäfer-Richter, G.: Readings in model based diagnosis. Morgan-Kauffman Pub., San Mateo (1992) 309–317
Oyeleye, O., Finch, F., Kramer, M.: Qualitative modeling and fault diagnosis of dynamic processes by MIDAS. Chemical Engineering Communications 96 (1990) 205–228
Cordier, M., Krivine, J., Laboire, P., Thiébaux, S.: Alarm processing and reconfiguration in power distribution systems. In: Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE-98. LNAI. Volume 1416., Springer-Verlag (1998) 230–241
Dousson, C., Gaborit, P., Ghallab, M.: Situation recognition: representation and algorithms. In: Proceedings of the 13th International Joint Conference on Artificial Intelligence IJCAI’93. (1993) 166–172
Alonso, C., Pulido, B., Acosta, G.: On Line Industrial Diagnosis: an attempt to apply Artificial Intelligence techniques to process control. In: 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE-98. LNAI. Volume 1415., Springer-Verlag (1998) 804–813
Alonso, C., Pulido, B., Acosta, G., Llamas, C.: On-line Industrial supervision and diagnosis, knowledge level description and experimental results. Expert Systems with Applications 20 (2001) 117–132
Schreiber, G., Akkermans, H., Anjewierden, A., de Hoog, R., Shadbolt, N., Van de Velde, W., Wielinga, B.: Knowledge Engineering and Management, The CommonKADS Methodology. The MIT Press (1999)
Console, L., Torasso, P.: On the co-operation between abductive and temporal reasoning in medical diagnosis. Artificial Intelligence in Medicine 3 (1991) 291–311
Console, L., Dupré, D.T.: On the dimensions of temporal model-based diagnosis. In: Proceedings of the DX’98. 9th Int. Workshop on Principles of Diagnosis. (1998) 16–23
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Alonso, C.J., Llamas, C., Maestro, J.A., Pulido, B. (2003). Diagnosis of Dynamic Systems: A Knowledge Model That Allows Tracking the System during the Diagnosis Process. In: Chung, P.W.H., Hinde, C., Ali, M. (eds) Developments in Applied Artificial Intelligence. IEA/AIE 2003. Lecture Notes in Computer Science(), vol 2718. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45034-3_21
Download citation
DOI: https://doi.org/10.1007/3-540-45034-3_21
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40455-2
Online ISBN: 978-3-540-45034-4
eBook Packages: Springer Book Archive