尤里卡沥青软化点人工智能软测量技术探索  

Investigation on Eureka pitch-softened-point measuring by artificial intelligent method

作　　者：束长好[1] 黄费喜[1] 张健[1] 陆新建[1] 彭飞[1] 

机构地区：[1]扬子石化股份有限公司炼油厂,江苏南京210048

出　　处：《南京工业大学学报（自然科学版）》2003年第4期97-101,共5页Journal of Nanjing Tech University(Natural Science Edition)

摘　　要：人工神经元网络(ANN)应用于软测量是人工智能方法在石化过程中成功应用的热点,ANN不需要系统模型就能映射复杂非线性关系,特别适合炼油生产过程的建模与预测工作,研究了用ANN对尤里卡沥青软化点进行软测量的方法,和现用的吴羽公司kθ法相比,ANN方法测量精度高,具有学习能力和联想记忆能力,健壮性好,它与生产装置的DCS硬件相结合能够达到优化生产控制的目的。Soft measuring by artificial neural network (ANN) is a focus of the petrochemical process successfully applied by artificial intelligent method. ANN can map the complicated non-linearity relations without systemized modeling and it especially appropriate for modeling and predicting of refining plant. This article presents the method of soft measuring Eureka pitch-softened-point by ANN, which is accurate and easy to learn, operate and remember compared with kθ method of KUREHA corporation, so it can optimize refining process control by combining with Distributed Control System (DCS).

关 键 词：尤里卡沥青软化点 软测量 人工神经元网络 ANN 

分 类 号：TE626.86[石油与天然气工程—油气加工工程] TP183[自动化与计算机技术—控制理论与控制工程]