摘要
汽油干点是石油加工过程中汽油质量的一个重要指标,但实际生产中还没有合适的可用于实时测量这一参数的仪器,本文运用软测量技术,通过BP人工神经网络建立了软测量模型,并嵌入到DCS控制系统中对汽油干点进行实时预测和推断,在实际应用中取得了良好的预测效果.
The endpoint of gasoline is an important index in the petroleum processing. At present,there is no applicable instrument to measure this parameter. In this paper, soft-sensing model is established based on BP artificial network to predict the endpoint of gasoline, which has good prediction results in the simulating tests.
出处
《吉林化工学院学报》
CAS
2012年第1期62-64,共3页
Journal of Jilin Institute of Chemical Technology
关键词
人工神经网络
软测量
汽油干点
artificial neural network
soft-sensing
gasoline endpoint
