DocumentCode :
979736
Title :
Control of a copper laser using neural networks
Author :
Buckley, J.M. ; Richardson, M.B.
Author_Institution :
Res. & Dev., Urenco (Capenhurst) Ltd., Chester, UK
Volume :
7
Issue :
3
fYear :
1996
fDate :
6/1/1996 12:00:00 AM
Firstpage :
145
Lastpage :
152
Abstract :
Urenco (Capenhurst) Ltd., has been running high-power copper lasers for several years owing to an interest in selective photo-ionisation for commercial enrichment. The main advantages of these lasers as pump sources for this process are their efficiency at high power and their high pulse repetition frequency. However, certain load discharge conditions have been found to greatly reduce the lifetimes of expensive laser modulator components and therefore increase the running costs and downtime of the lasers. This article describes the use of multiple coupled neural networks which, trained by humans with the required experience, are first able to identify load conditions likely to result in a reduction in the lifetime of the modulator components and then alter the load conditions to minimise the stress placed on the modulator.
Keywords :
closed loop systems; costing; industrial control; laser beam applications; learning (artificial intelligence); neurocontrollers; Urenco Ltd; closed loop control; copper laser control; downtime; high pulse repetition frequency; high-power copper lasers; laser modulator components; lifetime; load discharge conditions; modulator stress; multiple coupled neural networks; neural network training; neural networks; neurocontrol; pump sources; running costs; selective photo-ionisation; Closed loop systems; Costs; Industrial control; Laser applications; Learning systems; Neurocontrollers;
fLanguage :
English
Journal_Title :
Computing & Control Engineering Journal
Publisher :
iet
ISSN :
0956-3385
Type :
jour
DOI :
10.1049/cce:19960310
Filename :
503172
Link To Document :
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