| Feng, C.(1991).
Inducing Temporal Fault Diagnostic Rules from a Qualitative Model
In Proceedings Eighth International Workshop on Machine Learning ,
pp 403 - 406, Morgan Kaufmann, San Mateo, C.A.
Pearce D.A. (1988).
The induction of fault diagnosis systems from qualitative models.
In Proceedings Seventh National Conference on Artificial Intelligence,
Saint Paul, Minnesota.
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| In [Feng 91], ILP has been applied to a problem within the aerospace industry, namely the diagnosis of power-supply failures in a communications satellite.
The satellite recharges its batteries using solar energy. The charging system can be described through a qualitative model consisting of 40 components and 29 sensors [Pearce 88]. As the satellite orbits the Earth, its position relative to the Sun changes, driving its power-supply subsystem through four distinct stages: battery charging, solstice, eclipse, and battery reconditioning. Qualitative simulation makes it possible to predict behaviour of the power supply in each of these stages. By provoking simulated faults in the components, the simulation can generate examples of relations between a fault and the supply's behaviour. These examples form the present dataset, which served as an input to the ILP program Golem. Golem induced a set of rules for diagnosing power supply failures. In generating the examples, faults were provoked in all possible components, thus guaranteeing that the rules are complete and correct for all single faults.
Because the power-supply's behaviour changes with time, the formalism used to describe the examples is based on temporal logic which proves to be suitable for ILP learning.
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and GMD 