Title :
Fault diagnosis from first principles using model-based expert systems
Author_Institution :
R. Mail Res. Centre, Swindon, UK
Abstract :
Many humans analyze faults from first principles (sometimes subconsciously) if experiential knowledge is not available. Such analysis is based on an understanding of the functions of the components in a system and the inputs and outputs which pass between them. The paper discusses the issues arising from an investigation into the representation of this understanding in a model-based diagnostic expert system, which has been undertaken by the AI Group of the Royal Mail (Engineering) Research Centre
Keywords :
digital simulation; electronic equipment testing; expert systems; failure analysis; inference mechanisms; knowledge representation; Royal Mail; diagnostic expert system; digital simulation; fault diagnosis; inference mechanisms; knowledge representation; model-based expert systems; printer diagnosis; reasoning;
Conference_Titel :
Intelligent Fault Diagnosis - Part 2: Model-Based Techniques, IEE Colloquium on
Conference_Location :
London
