Artificial intelligence approaches to fault diagnosis
Artificial intelligence approaches to fault diagnosis
- Author(s): R.J. Patton and C.J. Lopez-Toribio
- DOI: 10.1049/ic:19981029
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- Author(s): R.J. Patton and C.J. Lopez-Toribio Source: IEE Colloquium Update on Developments in Intelligent Control, 1998 page ()
- Conference: IEE Colloquium Update on Developments in Intelligent Control
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. (12 pages)
Inspec keywords: fault diagnosis; artificial intelligence; control engineering
Subjects: Artificial intelligence (theory); Maintenance and reliability; Reliability
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