Title :
Artificial intelligence approaches to fault diagnosis
Author :
Patton, Ron J. ; Lopez-Toribio, C.J.
Author_Institution :
Sch. of Eng., Hull Univ., UK
Abstract :
Fault diagnosis of control engineering systems can be based upon the generation of signals which reflect inconsistencies between the fault-free and faulty system operation-so-called residual signals. This paper outlines some recent approaches to the generation of residual signals using methods of integrating quantitative and qualitative system knowledge, based upon AI techniques
Keywords :
fault diagnosis; AI; artificial intelligence; control engineering systems; fault diagnosis; knowledge integration; qualitative system knowledge; quantitative system knowledge; residual signal generation;
Conference_Titel :
Update on Developments in Intelligent Control (Ref. No. 1998/513), IEE Colloquium on
Conference_Location :
London
DOI :
10.1049/ic:19981029