CHANG Peng, WANG Pu, GAO Xue-jin, et al. Research on batch process monitoring based on multi-stage kernel pattern entropy projection technology[J]. Chinese Journal of Scientific Instrument, 2014, 35(7): 1654-1661. (in Chinese)
CHANG Peng, WANG Pu, GAO Xue-jin. Microbial pharmaceutical process monitoring based on projection kernel entropy component[J]. Information and Control,2014, 43(4): 490-494. (in Chinese)
QI Yong-sheng, WANG Pu, GAO Xue-jin, et al. Fault detection for fermentation process based on multiphase dynamic PCA [ J ]. Journal of Beijing University of Technology, 2012, 38(10): 1474-1481. (in Chinese)
[7]
CHEN J H, WANG W Y. Performance monitoring of MPCA based control for multivariable batch control processes[ J]. Taiwan Institute of Chemical Engineers, 2010, 41(4): 465-474.
[8]
DARWISH H W, ATTIA M I, ABDELHAMMEED A S, et al. Comparative ANNs with different input layers and GA- PLS study for simultaneous spectrofluorimetric determination of melatonin and pyridoxine HCl in the presence of melatonin's main impurity [ J]. Molecules,
[9]
2013, 18(1): 974-996.
[10]
GEERT G, JEF V, JAN F. Discriminating between critical and noncritical disturbances in ( Bio) chemical bach processes using multi-model fault detection and end-quality prediction [ J ]. Industrial and Engineering Chemistry Research, 2012, 51(1): 1237-1238.
[11]
NAES T, TOMIC O. Multi-block regression based on combination so for thogonalisation, PLS regressionand canonical correlation analysis [ J]. Chemometrics and Intelligent Laboratory Systems, 2013, 124: 32-42.
[12]
CHOI S W, LEE I B. Mutilblock PLS based localized process diagnosis[J]. Journal of Process Control, 2005, 3(1): 295-306.
[13]
MORI J C, YU J. Quality relevant nonlinear batch process performance monitoring using a kernel based multiway non-Gaussian latent subspace projection approach[J]. Journal of Process Control, 2014, 24 (1): 57-71.
[14]
ZHANG Y W, HU Z Y. Multivariate process monitoring and analysis based on multi-scale KPLS[J]. Chemical Engineering Research & Design, 2011, 89(12): 2667-2678.
[15]
ZHANG Y W, AN J Y, LI Z M. Modeling and monitoring for handling nonlinear dynamic processes [J]. Information Sciences, Chemical Engineer Science, 2013, 235(20): 97-105.
[16]
ZHANG Y W, TENG Y D, ZHANG Y. Complex process quality prediction using modifies kernel partial least squares[J]. Chemical Engineer Science, 2010, 65(1):2153-2158.
[17]
ZHANG X, YAN W, SHAO H. Nonlinear multivariate quality estimation and prediction based on kernel partial least squares[J] Industrial and Engineering Chemistry Research, 2008, 47(1): 1120-1131.
CHANG Peng, WANG Pu, GAO Xue-jin. Batch process monitoring and quality prediction based on multi-way kernel entropy PLS[J]. Journal of Beijing Universtiry of Technology, 2014, 40(6): 851-856. (in Chinese)
CHANG Peng, WANG Pu, GAO Xue-jin, et al. Batch process monitroing and quality prediction based on statistics pattern analysis and MKPLS [ J ]. Chinese Journal of Scientific Instrument, 2014, 35 (6): 1409-
[22]
1416. (in Chinese)
[23]
WANG J, HE Q. Multivariate statistical process monitoring based on statistics pattern analysis [ J ]. Industrial Engineering Chemical Research, 2010, 49(1): 7858-7869
[24]
HE Q, WANG J. Statistics pattern analysis: a new process monitoring framework and its application to semiconductor batch processes[J]. American Institute of Chemical Engineers, 2011, 57(1): 107-121.
[25]
PENG K X, ZHANG K, LI G, et al. Contribution rate plot for nonlinear quality related fault diagnosis with application to the hot strip mill process [ J]. Control Engineering Practice, 2013, 21 (4): 360-369.
[26]
AGUADO D, FERRER A, FERRER J, et al. Multivariate SPC of a sequencing batch reactor for wastewater treatment[J]. Chemometrics and Intelligent Laboratory Systems, 2007, 85(1): 82-93.
