| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10675813 | Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms | 2005 | 7 Pages |
Abstract
This paper introduces the detection method of principal element content (carbon, hydrogen and oxygen) in coal by using pulsed fast-thermal neutron analysis method (PFTNA). A system for the measurement of coal by PFTNA is also presented. The 14Â MeV pulsed neutron generator and a Bi4Ge3O12 (BGO) detector with a 4096 Multi-Channel Analyzer (MCA) were applied in this system. The detection model of element content in coal based on back-propagation (BP) neural network which is optimized by Genetic Algorithms (GAs) was put forward, and the research of verifying the model was made by comparing the practical measured data of coal in power plant. The results show that the detection precision of carbon, hydrogen and oxygen using this model is 0.3%, 0.2% and 0.4%, respectively.
Related Topics
Physical Sciences and Engineering
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Surfaces, Coatings and Films
Authors
Sang Hai-feng, Wang Fu-li, Liu Lin-mao, Sang Hai-jun,