[1]
|
JIANG Q,WANG B,YAN X.Multiblock independent component analysis integrated with Hellinger distance and Bayesian inference for non-Gaussian plant-wide process monitoring[J].Industrial & Engineering Chemistry Research,2015,54(9):2497-2508. |
[2]
|
HUANG Jian,YAN Xuefeng.Dynamic process fault detection and diagnosis based on dynamic principal component analysis,dynamic independent component analysis and Bayesian inference[J].Chemometrics and Intelligent Laboratory Systems,2015,148:115-127. |
[3]
|
HUANG Jian,YAN Xuefeng.Double-step block division plant-wide fault detection and diagnosis based on variable distributions and relevant features[J].Journal of Chemometrics,2015,29(11):587-605. |
[4]
|
LI W,YUE H H,VALLE-CERVANTES S,et al.Recursive PCA for adaptive process monitoring[J].Journal of Process Control,2000,10(5):471-486. |
[5]
|
赵忠盖,刘飞.动态因子分析模型及其在过程监控中的应用[J],化工学报,2009,60(1):183-186.
|
[6]
|
HYVÄRINEN A,OJA E.Independent component analysis algorithms and applications[J].Neural Networks,2000,13(4):411-430. |
[7]
|
LEE J M,YOO C K,LEE I B.Statistical process monitoring with independent component analysis[J].Journal of Process Control,2004,14(5):467-485. |
[8]
|
刘雪琴,谢磊,张建明,等.基于ICA-SVDD的统计过程监控及其在化工过程中的应用[C]//2006全国石油化工生产安全与控制学术交流会.北京:中国化工学会,2006:21-25.
|
[9]
|
GE Zhiqiang,SONG Zhihuan.Process monitoring based on independent component analysis-principal component analysis (ICA-PCA) and similarity factors[J].Industrial & Engineering Chemistry Research,2007,46(7):2054-2063. |
[10]
|
尹雪岩,刘飞.基于DIFA的动态非高斯过程监控方法及应用[J].化工学报,2011,62(5):1345-1351.
|
[11]
|
ATTIAS H.Independent factor analysis[J].Neural Computation,1999,4(11):803-851. |
[12]
|
尹雪岩,刘飞.独立因子分析方法在过程监控中的应用[J].计算机与应用化学,2010,27(10):1353-1356.
|
[13]
|
LI X,YANG Y,ZHANG W.Statistical process monitoring via generalized non-negative matrix projection[J].Chemometrics and Intelligent Laboratory Systems,2013,121:15-25. |
[14]
|
赵忠盖,刘飞.因子分析及其在过程监控中的应用[J].化工学报,2007,58(4):970-974.
|
[15]
|
SHEN Y,DING S X,HAGHANI A,et al.A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process[J]. Journal of Process Control,2012,22(9):1567-1581. |
[16]
|
DOWNS J J,VOGEL E F.A plant-wide industrial process control problem[J].Computers & Chemical Engineering,1993,17(3):245-255. |
[17]
|
JIANG Q,YAN X.Probabilistic weighted NPE-SVDD for chemical process monitoring[J].Control Engineering Practice,2014,28:74-89. |
[18]
|
BATHELT A,RICKER N L,JELALI M.Revision of the Tennessee Eastman process model[J].International Symposium on Advanced Control of Chemical Processes,2015,48(8):309-314. |
[19]
|
江伟,王昕,王振雷.基于LTSA和MICA与PCA联合指标的过程监控方法及应用[J].化工学报,2015,66(12):4895-4903.
|
[20]
|
JIANG Q,YAN X.Non-Gaussian chemical process monitoring with adaptively weighted independent component analysis and its applications[J].Journal of Process Control,2013,23(9):1320-1331. |
[21]
|
JIANG Q,YAN X,LV Z,et al.Independent component analysis-based non-Gaussian process monitoring with preselecting optimal components and support vector data description[J].International Journal of Production Research,2014,52(11):3273-3286. |
[22]
|
杨正永,王昕,王振雷.基于LTSA和联合指标的非高斯过程监控方法及应用[J].化工学报,2015,66(4):1370-1379.
|