Diagnosis of Complex Agricultural Machines

Abstract Agricultural machines are more and more complex. This states a problem of reliability, essentially due to diagnosis difficulties. This paper describes a modelling method adapted to these machines, based on structural, symbolical and behavioural abstractions. This way of knowledge representation is used by a case based reasoning which produces some more or less abstracted hypotheses, feeding a classical deductive diagnosis. First tests of the hypotheses generator have given some encouraging results.