EPSRC Reference: |
GR/L60753/01 |
Title: |
FUZZY NEURAL NETWORKS APPROACH TO GENERATOR PROTECTION AGAINST INTERNAL FAULTS |
Principal Investigator: |
Aggarwal, Professor RK |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Electronic and Electrical Engineering |
Organisation: |
University of Bath |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 January 1998 |
Ends: |
16 April 2001 |
Value (£): |
120,615
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EPSRC Research Topic Classifications: |
Power Sys Man, Prot & Control |
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EPSRC Industrial Sector Classifications: |
Energy |
No relevance to Underpinning Sectors |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
The research project is a cooperative venture between the University of Bath and GEC Alsthom Protection and Control which is a world leader in the manufacture of protection and control equipments for power systems. The main objective of the project is to research into a new technique, fundamentally different from conventional methods, for accurately and reliably detecting generator winding faults (in particular in medium-size generators) that will minimise damage and expedite repairs to damaged machines, thereby keeping both outage times and maintenance costs of plants down in generating companies throughout the world. The fundamental basis of the work will be to research into FNN-based techniques, capable of dealing with all types of practically encountered generator winding faults. The ultimate aim is to research a technique capable of dealing with all types of generator winding faults. Finally, the technique will be implemented on a low-cost standard hardware to prove its performance in real time.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.bath.ac.uk |