An artificial intelligence system of trouble diagnosis for aircraft engines
Reported here is about the trouble diagnosis system for AN-24 aircraft engine which has been realized by inputting the experiences of the repair mechanics or experts of the engine as a computer software. The system is composed of following four sections which are called ''model''; a phenomena model, an inference model, a learning model, and an interpretation model. Therefore, the system is called as ''model diagnosis system''. These four models are relatively independent which makes parallel operation, easy debugging, and addition of new knowledge possible. The experience of the engine experts has been stored initially to outer knowledge base in the computer. Intermidiate knowledge which arises on the process of the inference is treated at inner knowledge base. The inner knowledge base adopts a blackboard structure. This makes the system not only able to diagnose the vague preconditioned reason, but also to diagnose the unpreconditioned one by Learning. The validity of the system was proved from some experiments.
artificial intelligence diagnosis aircraft engine knowledge base