| EPSRC Reference: |
GR/L16651/01 |
| Title: |
THE INCLUSION OF POSTERIOR KNOWLEDGE IN FAULT DIAGNOSIS |
| Principal Investigator: |
Harrison, Professor RF |
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| Department: |
Automatic Control and Systems Eng |
| Organisation: |
University of Sheffield |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
27 August 1996 |
Ends: |
26 August 1999 |
Value (£): |
138,334
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Summary on Grant Application Form |
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This work aims to provide methodological and software tools for the establishment of neural network-based diagnostic aids which can revise their recommendations in response to new information. Systems which can operate with small initial data samples but can continue to improve their performance in situ are needed because appropriate data are usually rare at development. The proposed solution is based on the Adaptive Resonance Theory family of neural networks which possesses the necessary properties.If successful, the resulting tools will have general applicability in diagnostic and classification tasks and the generic tools will be evaluated on a series of fault detection problems in gas turbine power plant. A number of key issues in neural network learning and performance will be addressed. The importance of the work will be in helping to overcome what is seen by potential end users as a major shortcoming of existing techniques. Furthermore, owing to its capacity for perpetual self-organisation, the development of decision aids can be made less reliant on computer experts and more so on domain experts and potential end users.Key Words: Artificial Intel, Control, Machinery, Neural Networks, Fault Detection, Self Organisation
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.shef.ac.uk |