Making use of process tomography data for multivariate statistical process control
Making use of process tomography data for multivariate statistical process control
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DOI：
10.1002/aic.12443
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发表时间：
2011-09
期刊：
影响因子：
3.7
通讯作者：
Bundit Boonkhao;Ruifa Li;X. Wang;R. Tweedie;K. Primrose
中科院分区：
文献类型：
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作者：
Bundit Boonkhao;Ruifa Li;X. Wang;R. Tweedie;K. Primrose
描述了一种有效利用在线过程层析成像测量进行过程监测的新策略。配备有16个电极的电阻层析成像（ERT）传感系统每25 ms提供104个电导率测量。该数据传统上用于构建用于显示目的的图像。在这项研究中，ERT数据用于多变量统计过程控制。使用主成分分析法处理预定义正常操作条件下的数据。压缩后的数据用于推导两个统计量，T2和平方预测误差（SPE）。T2和SPE图预测被监测过程在混合质量方面从先前状态或所谓的正常操作状态发生统计学显著变化的概率。该方法通过参考向日葵油/水乳化过程的案例研究来说明。© 2010美国化学工程师学会AIChE J，2011
A novel strategy for making effective use of on-line process tomography measurements for process monitoring is described. The electrical resistance tomography (ERT) sensing system equipped with sixteen electrodes provides 104 conductivity measurements every 25 ms. The data has traditionally been used for construction of images for display purpose. In this study, ERT data was used for multivariate statistical process control. Data at predefined normal operational conditions was processed using principal component analysis. The compressed data was used to derive two statistics, T2 and squared prediction error (SPE). T2 and SPE charts predict the probability that the process being monitored has undergone statistically significant changes from previous state or the so-called normal operational state, in terms of mixing quality. The methodology is illustrated by reference to a case study of a sunflower oil/water emulsion process. © 2010 American Institute of Chemical Engineers AIChE J, 2011