基于工业色谱仪的精馏脱炔烃塔软测量建模  

Soft Sensor Modeling of Alkynes Removal Distillation Tower Based on Gas Chromatograph

作　　者：储琴[1] 程明霄[1] 

机构地区：[1]南京工业大学自动化学院,南京210009

出　　处：《化工自动化及仪表》2010年第10期37-40,46,共5页Control and Instruments in Chemical Industry

摘　　要：提出一种基于工业色谱仪的软测量建模方法,并针对碳五馏分分离过程中的精馏脱炔烃塔塔底成分估计问题,建立了合适的工业软测量模型。介绍了工业色谱仪在线质量检测原理和LM-BP神经网络模型的建立,并利用工业色谱仪在线检测的质量数据进行系统的在线和周期性模型更新,提高了软测量模型的在线估计精度。研究结果表明,基于工业色谱仪的LM-BP神经网络模型是一种有效的软测量建模方法。The soft sensor modeling method based on gas chromatograph was proposed.In accordance with the task of composition estimation for alkynes removal distillation tower in the process of C5 separation,appropriate soft sensor model was established.The on-line quality detection principle of gas chromatograph and LM-BP neural network modeling was introduced.By adopting on-line quality data from gas chromatograph,on-line optimization of the system and the update of the model were carried out.Thus on-line estimation accuracy of soft sensor mode was enhanced.The result shows LM-BP neural network based on gas chromatograph is an efficient modeling method for soft sensor.

关 键 词：工业色谱仪 软测量 精馏脱炔烃塔 LM-BP神经网络 建模 

分 类 号：TH301[机械工程—机械制造及自动化]