摘要
针对常压塔航煤比重在线质量仪表存在滞后大、易出现故障的缺点 ,提出了运用动态递归神经网络 ,根据实测的温度、流量、压力等过程参数 ,在线估计航煤比重 。
In accordance with that on-line specific gravity quality instrument of aviation kerosene in atmospheric distillation tower exists the shortcoming of long time delay and easy trouble, the on line estimation of aviation kerosene specific gravity based on diagonal recurrent neural network is proposed in this paper. The input variables of neural network are temperature, flow, press, which can been measured. The estimation of aviation kerosene specific gravity provides foundation for quality closed control.
出处
《计算机自动测量与控制》
CSCD
2001年第2期50-51,53,共3页
Computer Automated Measurement & Control
关键词
炼油厂
航空煤油
在线估计
比重
动态递归神经网络
diagonal recurrent neural network(DRNN)
atmospheric distillation tower
specific gravity
aviation kerosene
on line estimation
