[1]周东华, 李钢, 李元. 数据驱动的工业过程故障诊断技术[M]. 北京:科学出版社, 2011:161170.
[2]周东华, 叶银忠. 现代故障诊断与容错控制[M]. 北京:清华大学出版社, 2000:2444.
[3]Jolliffe I T. Principal component analysis, Second Edition [M]. London: Springer, 2002:1012.
[4]Qin S J. Survey on datadriven industrial process monitoring and diagnosis [J]. Annual Reviews in Control, 2012, 36(2):220234.
[5]Wen C L, Zhou F N, Wen C B, et al. An extended multiscale principal component analysis method and application in anomaly detection [J].Chinese Journal of Electronics, 2012, 21(3):471476.
[6]Qin S J, McAvoy T J. Nonlinear PLS modeling using neural networks [J]. Computers and Chemical Engineering, 1992, 16(4):379391.
[7]Rosipal R, Trejo L J. Kernel parital least squares regression in reproducing kernel hibert space [J]. Journal of Machine Learning Research, 2001(2):97123.
[8]胡益, 王丽, 马贺贺, 等. 基于核PLS方法的非线性过程在线监控 [J]. 化工学报, 2011, 62(9):25552561.
HU Yi, WANG Li, MA Hehe, et al. Online nonlinear process monitoring using kernel partial least squares [J]. CIESC Journal, 2011, 62(9):25552561.
[9]Peng K X, Zhang K, Li G. Qualityrelated process monitoring based on total kernel PLS model and its industrial application [J]. Mathematical Problems in Engineering, 2013:114.
[10]Zhang Y W, Sun R R, Fan Y P. Fault diagnosis of nonlinear process based on KCPLS reconstruction [J]. Chemometrics and Intelligent Laboratory Systems, 2015, 140:4960.
[11]Zhou D H, Li G, Qin S J. Total projection to latent structures for process monitoring [J]. AIChE Journal, 2010, 56(1):168178.
[12]Zhao C H, Sun Y X. The multispace generalization of total projection to latent structures (MsTPLS) and its application to online process monitoring [C]∥2013 10th IEEE International Conference on ICCA. USA: IEEE, 2013: 14411446.
[13]Qin S J, Zheng Y Y. Qualityrelevant and processrelevant fault monitoring with concurrent projection to latent structures [J]. AIChE Journal, 2013, 59(2):496504.
[14]Hu J, Wen C L, Li P, et al. Direct projection to latent variable space for fault detection [J]. Journal of the Franklin Institute, 2014, 351(3):12261250.
[15]Yin S, Ding X S, Zhang P, et al. Study on modifications of PLS approach for process monitoring [C]∥Proc of 18th IFAC World Congress. Milano, Italy: IFAC, 2011.
[16]Li G, Qin S J, Zhou D H. Geometric properties of partial least squares for process monitoring [J]. Automatica, 2010, 46(1):204210.
[17]Nomikos P, MacGregor J F. Multivariate SPC charts for monitoring batch process [J]. Technometrics, 1995, 37:4159.
[18]Downs J J, Vogel E F. A plantwide industrial process control problem [J]. Computer and Chemical Enginerring, 1993, 17(3):245255.
[19]Chiang L H, Russell E, Braaz R D. Fault detection and diagnosis in industrial systems [M]. London: Springer, 2001. |