Handling Qualitative Aspects of Human Knowledge in Diagnosis

Knowledge involved in diagnosis of real complex systems comes from human experts and requires appropriate discrete and qualitative representation. The large amount of information resulted is difficult to manage and prepare to enter the diagnosis system without the help of an appropriate tool. The paper proposes a knowledge elicitation scheme for multifunctional conductive flow systems ’ faulty behaviour, along with appropriate representation of instance manifestations in a semi-qualitative manner, suited to human diagnostician conceptual view. Computer Aided Knowledge Elicitation (CAKE) tool proposed copes with knowledge involved in diagnosis . A case study on a hydraulic installation is finally presented.