化工学报2019，Vol.70Issue(z1)：141-149,9.DOI:10.11949/j.issn.0438⁃1157.20181369
基于Ms-LWPLS的化工过程网络化性能分级评估方法
Networked grading performance assessment method of chemical process based on Ms-LWPLS
摘要
Abstract
A networked performance assessment method based on multi-space locally weighted projection to latent structures (Ms-LWPLS) is proposed to solve the nonlinear relationship between input and output data of chemical process. This method divides the historical training datasets into different sets of performance grades, extracting the process changes of different performance grade of training datasets by Ms-LWPLS method. This method obtains the latent structures accurately by matching the training datasets and performance grade labels through the non-linear networked structure. The"off-line modeling"is achieved by the trained neural network. With the model obtained, the sliding window is used as the assessment unit, working as the input data into the trained neural network model. The current performance grade is identified according to the network output and the transition performance coefficient is constructed. The steady-state performance grades and the transition performance grades are recognized and distinguished. Finally, the method is applied to the online performance assessment of ethylene cracking process, which shows the effectiveness and accuracy of the performance assessment method proposed.关键词
多数据空间/局部加权潜结构映射/非线性/神经网络/过渡/稳态/在线评估Key words
multi-space/ locally weighted projection to latent structures/ nonlinearity/ neural network/ transition/steady state/ online assessment分类
信息技术与安全科学引用本文复制引用
曹晨鑫,杜玉鹏,王昕,王振雷..基于Ms-LWPLS的化工过程网络化性能分级评估方法[J].化工学报,2019,70(z1):141-149,9.基金项目
国家自然科学基金项目(61673268) （61673268）
国家自然科学基金重点项目(61533003) （61533003）
国家自然科学基金重大项目(61590922) （61590922）
中央高校基本科研业务费专项资金(222201814043) （222201814043）
