摘要
介绍了中子法快速检测煤中碳含量的方法。基于遗传算法(GA)优化的BP神经网络建立了煤中碳含量的检测模型,并结合电厂锅炉燃烧用煤的实测数据进行模型的验证研究。结果表明,该方法对煤中碳含量的检测精度达到了0.5%。
The detection method of carbon content in coal with neutron method is introduced. The detection model of carbon content in coal based on BP neural network, which is optimized by genetic algorithms, is put forward. A study for verifying the model is made by comparison with the practical measured data of coal in power plant. The results show that the detection precision is 0.5 % with this model.
出处
《计量学报》
EI
CSCD
北大核心
2006年第1期73-76,共4页
Acta Metrologica Sinica
基金
国家973计划(2002CB312200)
关键词
计量学
碳含量
遗传算法
BP神经网络
中子法
特征γ射线
Metrology
Genetic algorithms； Carbon content
BP neural network
Neutron method
Characteristic γ-ray
