A methodology for the development of model-based diagnostic systems

The development of application systems for fault diagnosis has attracted worldwide interest in many different research areas. In particular, advanced techniques for finding faults through the use of explicit structural and/or behavioural models of the physical system to be diagnosed have been developed both in the area of control engineering and in the field of artificial intelligence. Although many approaches to creating model-based diagnostic systems (MBDS) exist, as yet, no clear methodology is available for the selection of an appropriate approach to solve individual given diagnostic problems. We have therefore been developing a specification methodology that essentially comprises a taxonomy of diagnostic tasks, a taxonomy of model-based systems, and a set of guidelines that provides a mapping from the former to the latter, Our aim is to provide a method by which existing MBDS tools and techniques may be combined within a generic architecture in a principled manner to produce effective diagnostic systems for given applications. The structure of the methodology has been derived in part from the top level architectural design of ARTIST, a generic model-based diagnostic toolkit that combines a wide variety of model based diagnostic (MBD) tools. This architecture is based upon the three main types of knowledge that are necessary for the construction of model based diagnostic systems