Troubleshooting CFM 56-3 engines for the Boeing 737 using CBR and data-mining
This paper describes the industrialisation of a software system to support fault diagnosis of the CFM 56 -3 aircraft engine. The system uses data-mining techniques known as induction and case based reasoning which exploit failure descriptions that are stored in a case base. A first prototype using the induction technique applied on an initial case base has been achieved. The paper presents the main characteristics of the CBR and induction techniques. The modelling of the engine failures and the process of feeding the case base are given next. The system is intended to be used by airline maintenance staff and CFMI specialists. A user friendly environment has been implemented to allow an optimum use of the system as a troubleshooting support.
Unable to display preview. Download preview PDF.
- Althoff, K.-D., Auriol, E., Barletta, R. & Manago, M.A Review of Industrial Case-Based Reasoning Tools. A. Goodall (Ed.), AI Intelligence, Oxford, 1995.Google Scholar
- .Auriol, E., Wess, S., Althoff, K.-D., Manago, M. & Traphöner, R.. “Inreca: A seamlessly integrated system based on inductive inference and case-based reasoning”. ICCBR 95, First International Conference on Case-Based Reasoning, Veloso M. & Aamodt A. (eds), Springer Verlag, Heidelberg, 1995.Google Scholar
- .Vingerhoeds, R.A., Janssens, P., Netten, B.D. & Fernandez-Montesinos “Enhancing off-line and on-line condition monitoring and fault diagnosis”. Control Eng. Practice, Vol 3, No. 11, pp. 1515–1528, 1995. Elsevier Science Ltd.Google Scholar