Abstract Data-driven tools, such as principal component analysis （PCA） and independent component analysis （ICA） have been applied to different benchmarks as process monitoring methods. The difference between the t...Abstract Data-driven tools, such as principal component analysis （PCA） and independent component analysis （ICA） have been applied to different benchmarks as process monitoring methods. The difference between the two methods is that the components of PCA are still dependent while ICA has no orthogonality constraint and its latentvariables are independent. Process monitoring with PCA often supposes that process data or principal components is Gaussian distribution. However, this kind of constraint cannot be satisfied by several practical processes. To ex-tend the use of PCA, a nonparametric method is added to PCA to overcome the difficulty, and kernel density estimation （KDE） is rather a good choice. Though ICA is based on non-Gaussian distribution intormation, .KDE can help in the close monitoring of the data. Methods, such as PCA, ICA, PCA.with .KDE（KPCA）, and ICA with KDE,（KICA）, are demonstrated and. compared by applying them to a practical industnal Spheripol craft polypropylene catalyzer reactor instead of a laboratory emulator.展开更多
采用有机溶剂法研究香榧假种皮提取物的提取工艺。确定提取溶剂后,在单因素试验基础上,选取对提取率影响较显著的提取时间、提取温度、液料比3个因素作为变量,以香榧假种皮提取物得率为指标,采用Box-Behnken试验设计方法做三因素三水平...采用有机溶剂法研究香榧假种皮提取物的提取工艺。确定提取溶剂后,在单因素试验基础上,选取对提取率影响较显著的提取时间、提取温度、液料比3个因素作为变量,以香榧假种皮提取物得率为指标,采用Box-Behnken试验设计方法做三因素三水平试验,得到香榧假种皮提取物的提取工艺。利用Design Expert软件得到回归方程的预测模型,做响应面分析,确定香榧假种皮提取物的提取工艺：石油醚（沸程30-60℃）为溶剂,粉碎度40目,提取时间2.6 h,液料比11 m L/g,提取温度51℃。在此条件下提取物平均得率为18.28%。经GCMS分析,香榧假种皮提取物的主要成分为二萜类物质,其次为倍半萜类和单萜类物质。展开更多
基金Supported by the National Natural Science Foundation of China （No.60574047） and the Doctorate Foundation of the State Education Ministry of China （No.20050335018）.
文摘Abstract Data-driven tools, such as principal component analysis （PCA） and independent component analysis （ICA） have been applied to different benchmarks as process monitoring methods. The difference between the two methods is that the components of PCA are still dependent while ICA has no orthogonality constraint and its latentvariables are independent. Process monitoring with PCA often supposes that process data or principal components is Gaussian distribution. However, this kind of constraint cannot be satisfied by several practical processes. To ex-tend the use of PCA, a nonparametric method is added to PCA to overcome the difficulty, and kernel density estimation （KDE） is rather a good choice. Though ICA is based on non-Gaussian distribution intormation, .KDE can help in the close monitoring of the data. Methods, such as PCA, ICA, PCA.with .KDE（KPCA）, and ICA with KDE,（KICA）, are demonstrated and. compared by applying them to a practical industnal Spheripol craft polypropylene catalyzer reactor instead of a laboratory emulator.
文摘采用有机溶剂法研究香榧假种皮提取物的提取工艺。确定提取溶剂后,在单因素试验基础上,选取对提取率影响较显著的提取时间、提取温度、液料比3个因素作为变量,以香榧假种皮提取物得率为指标,采用Box-Behnken试验设计方法做三因素三水平试验,得到香榧假种皮提取物的提取工艺。利用Design Expert软件得到回归方程的预测模型,做响应面分析,确定香榧假种皮提取物的提取工艺：石油醚（沸程30-60℃）为溶剂,粉碎度40目,提取时间2.6 h,液料比11 m L/g,提取温度51℃。在此条件下提取物平均得率为18.28%。经GCMS分析,香榧假种皮提取物的主要成分为二萜类物质,其次为倍半萜类和单萜类物质。
