摘要
讨论了如何建立聚丙烯熔融指数软测量模型及模型更新问题.首先根据聚丙烯反应器中的氢气浓度划分操作域,对于每个操作域,用一种新的非线性部分最小二乘方法建立熔融指数软测量子模型,然后将各个子模型进行组合,建立全局模型.为了使模型适应过程的变化,提出一种递推非线性部分最小二乘算法,利用新获得的数据对原模型进行更新.同时基于滑动窗方法,提出模型在线估计和更新策略.实际应用结果表明,模型取得了很好的估计性能,计算精度满足工业生产的实际要求.
Operating regime based soft sensing model of polypropylene melt flow rate （MFR） was developed. First, different operating regimes were determined according to the concentration of hydrogen in the reactor. Then for each operating regime, a nonlinear PLS （NLPLS） model was built by combining PLS with RBF networks. Finally, all the sub-models were combined to formulate the global model. To deal with the problem that the process changed with time, a recursive nonlinear PLS （RNPLS） algorithm was proposed to update the model to adapt process changes. In addition, an on-line model estimation and updating procedure based on moving window approach was proposed. The proposed method was used in an actual plant, and the results showed that the model achieved quite good performance and the accuracy of the model could satisfy the practical need.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2005年第10期1915-1921,共7页
CIESC Journal
