A fault diagnosis method for multimode processes based on ICA mixture models

[1]  Xuefeng Yan,et al.  Nonlinear plant-wide process monitoring using MI-spectral clustering and Bayesian inference-based multiblock KPCA , 2015 .

[2]  Song Bin.  Fault detection for chemical process based on LSNPE method , 2014 .

[3]  A. Kraskov,et al.  Estimating mutual information. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Steven X. Ding,et al.  A Review on Basic Data-Driven Approaches for Industrial Process Monitoring , 2014, IEEE Transactions on Industrial Electronics.

[5]  Xuemin Tian,et al.  Multimode Process Fault Detection Using Local Neighborhood Similarity Analysis , 2014 .

[6]  Terrence J. Sejnowski,et al.  ICA Mixture Models for Unsupervised Classification of Non-Gaussian Classes and Automatic Context Switching in Blind Signal Separation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Qinghua Li,et al.  Process monitoring based on factor analysis: Probabilistic analysis of monitoring statistics in presence of both complete and incomplete measurements , 2015 .

[8]  Hanyuan Zhang,et al.  A local and global statistics pattern analysis method and its application to process fault identification , 2015 .

[9]  Furong Gao,et al.  Review of Recent Research on Data-Based Process Monitoring , 2013 .

[10]  Zhi-huan Song,et al.  Mixture Bayesian regularization method of PPCA for multimode process monitoring , 2010 .

[11]  Bhaskar D. Rao,et al.  Newton method for the ICA mixture model , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[12]  Ahmet Palazoglu,et al.  An adaptive multimode process monitoring strategy based on mode clustering and mode unfolding , 2013 .

[13]  Zhiqiang Ge,et al.  Multimode process monitoring based on Bayesian method , 2009 .

[14]  Xuemin Tian,et al.  Sparse Kernel Locality Preserving Projection and Its Application in Nonlinear Process Fault Detection , 2013 .

[15]  Nina F. Thornhill,et al.  Finding the Direction of Disturbance Propagation in a Chemical Process Using Transfer Entropy , 2007, IEEE Transactions on Control Systems Technology.

[16]  Ahmet Palazoglu,et al.  Improved ICA for process monitoring based on ensemble learning and Bayesian inference , 2014 .

[17]  Joseph T. Lizier,et al.  Directed Information Measures in Neuroscience , 2014 .

[18]  Jie Yu,et al.  A new fault diagnosis method of multimode processes using Bayesian inference based Gaussian mixture contribution decomposition , 2013, Eng. Appl. Artif. Intell..

[19]  ChangKyoo Yoo,et al.  Statistical process monitoring with independent component analysis , 2004 .

[20]  Lei Xie,et al.  Multimode process monitoring with PCA mixture model , 2014, Comput. Electr. Eng..