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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | McDonald, J.R. Moyes, A. Georgin, E. |
| Copyright Year | 1996 |
| Description | Author affiliation: Centre for Electr. Power Eng., Strathclyde Univ., Glasgow, UK (McDonald, J.R.; Moyes, A.; Georgin, E.) |
| Abstract | Effective monitoring and control strategies are essential to maintaining efficient turbine-generator operation. This paper outlines an approach to achieving this aim by integrating a number of artificial intelligence (AI) techniques. An integrated architecture is described and two case studies are presented which demonstrate the potential of utilising such an approach. The paper concludes with a discussion of issues crucial to the further application of AI techniques to turbine-generator monitoring and control. |
| Starting Page | 151 |
| Ending Page | 155 |
| File Size | 489073 |
| Page Count | 5 |
| File Format | |
| ISBN | 078033115X |
| DOI | 10.1109/ISAP.1996.501060 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1996-01-28 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Knowledge engineering Decision support systems Power engineering Knowledge acquisition Problem-solving Expert systems Artificial intelligence Turbines Monitoring Diagnostic expert systems |
| Content Type | Text |
| Resource Type | Article |
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