1 MacGregor, J.F., Kourti, T., “Statistical process control of multivariate processes”, Control Engineering Practice, 3, 403-414(1995). 2 MacGregor, J.F., Kourti, T., Nomikos, P., “Analysis, monitoring and fault diagnosis of industrial processes using multivariate statistical projection methods”, In: Proceedings of 13th IFAC World Congress, San Francisco, USA(1996). 3 Russell, E.L., Chiang, L.H., Braatz, R.D., Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes, Springer-Verlag, New York(2000). 4 Kano, M., Hasebe, S., Hashimoto, I., “Statistical process monitoring based on dissimilarity of process data”, AIChE Journal, 48, 1231-1240(2002). 5 Venkatasubramanian, V., Rengaswamy, R., Yin, K., Kavuri, S.N., “A review of process fault detection and diagnosis Part Ⅲ: Process history data based methods”, Computers & Chemical Engineering, 27, 327-346(2003). 6 Xie, L., Zhang, J., Wang, S., “Investigation of dynamic multivariate chemical process monitoring”, Chin. J. Chem. Eng., 14, 559-568(2006). 7 Xiong, L., Liang, J., Qian, J., “Multivariate statistical process monitoring of an industrial polypropylene catalyzer reactor with component analysis and kernel density estimation”, Chin. J. Chem. Eng., 15, 524-532(2007). 8 Dunia, R., Qin, S.J., Edgar, T.F., McAvoy, T.J., “Identification of faulty sensors using principal component analysis”, AIChE Journal, 42, 2797-2812(1996). 9 Dunia, R., Qin, S.J., “Subspace approach to multidimensional fault identification and reconstruction”, AIChE Journal., 44, 1813-1831(1998). 10 Kourti, T., Lee, J., MacGregor, J.F., “Experiences with industrial applications of projection methods for multivariate statistical process control”, Computers & Chemical Engineering, 20, S745-S750(1996). 11 Wise, B.M., Gallagher, N.B., “The process chemometrics approch to process monitoring and fault detection”, Journal of Process Control, 6, 329-348(1996). 12 Kourti, T., “Application of latent variable methods to process control and multivariate statistical process control in industry”, International Journal of Adaptive Control and Signal Processing, 19, 213-246(2005). 13 Gertler, J., Singer, D., “A new structural framework for parity equation-based failure-detection and isolation”, Automatica, 26, 381-388(1990). 14 Gertler, J., Li, W., Huang, Y., McAvoy, T., “Isolation enhanced principal component analysis”, AIChE Journal, 45, 323-334(1999). 15 Patton, R.J., Frank, P.M., Clark, R.N., Issues of Fault Diagnosis for Dynamic Systems, Springer, London(2000). 16 Gertler, J., McAvoy, T.J., “Principal component analysis and parity relations—A strong duality”, In: IFAC Safeprocess Symp., Hull, UK(1997). 17 Huang, Y., Gertler, J., McAvoy, T.J., “Sensor and actuator fault isolation by structured partial PCA with nonlinear extensions”, Journal of Process Control, 10, 459-469(2000). 18 Gertler, J., Cao, J., “Design of optimal structured residuals from partial principal component models for fault diagnosis in linear systems”, Journal of Process Control, 15, 585-603(2005). 19 Li, R., Rong, G., “Fault isolation by partial dynamic principal component analysis in dynamic process”, Chin. J. Chem. Eng., 14, 486-493(2006). 20 Gertler, J., Cao, J., “PCA-based fault diagnosis in the presence of control and dynamics”, AIChE Journal, 50, 388-402(2004). 21 Qin, S.J., Li, W.H., “Detection, identification, and reconstruction of faulty sensors with maximized sensitivity”, AIChE Journal, 45, 1963-1976(1999). 22 Kwan, C., Xu, R., “A note on simultaneous isolation of sensor and actuator faults”, IEEE Transactions on Control Systems Technology, 12, 183-192(2004). 23 Lin, W.L., Qin, S.J., “Optimal structured residual approach for improved faulty sensor diagnosis”, Industrial & Engineering Chemistry Research, 44, 2117-2124(2005). 24 Cheng, H., Nikus, M., Jamsa-Jounela, S.L., “Evaluation of PCA methods with improved fault isolation capabilities on a paper machine simulator”, Chemometrics and Intelligent Laboratory Systems, 92, 186-199(2008). 25 Yoon, S., McGregor, J.F., “Fault dignosis with multivariate statistical models part I: using steady state fault signatures”, Journal of Process Control, 11, 384-400(2001). 26 Downs, J.J., Vogel, E.F., “A plant-wide industrial process control problem”, Computers & Chemical Engineering, 17, 245-255(1993). 27 McAvoy, T.J., Ye, N., “Base control for the Tennessee Eastman problem”, Computers & Chemical Engineering, 18, 383-413(1994). |