Author(s): D. Lane & P.J. Nolan
Because of the demands of modern automated manufacturing systems and the
serious implications of machine down time, there has been much attention
focussed lately of the early diagnosis of faults.
Many methodologies have been
suggested and tested, however up until now little research on the applicability
of new methodologies has been completed.
Our research seeks to rectify this situation.
This paper describes a
diagnosis approach which uses a fault dictionary derived from detailed
simulation modelling of a small electro-mechanical subsystem typically found
in machine tool applications.
Faults are then classified using one of the new
methodologies and the performance evaluated.
In this paper comparative
results for a variety of methods including Neural Networks, Lear...
Size: 76 kb
Paper DOI: 10.2495/AI970331
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