-
2
-
-
77954376366
-
Progress of data-driven and knowledge-driven process monitoring and fault diagnosis for industry process
-
Liu Qiang, Chai Tian-You, Qin Si-Zhao, Zhao Li-Jie. Progress of data-driven and knowledge-driven process monitoring and fault diagnosis for industry process. Control and Decision, 2010, 25(6): 801-807, 813
-
(2010)
Control and Decision
, vol.25
, Issue.6
-
-
Liu, Q.1
Chai, T.-Y.2
Qin, S.-Z.3
Zhao, L.-J.4
-
3
-
-
0242354134
-
Statistical process monitoring: Basics and beyond
-
Qin S J. Statistical process monitoring: basics and beyond. Journal of Chemometrics, 2003, 17(8-9): 480-502
-
(2003)
Journal of Chemometrics
, vol.17
, Issue.8-9
, pp. 480-502
-
-
Qin, S.J.1
-
4
-
-
77956075435
-
Reconstruction-based contribution for process monitoring with kernel principal component analysis
-
Alcala C F, Qin S J. Reconstruction-based contribution for process monitoring with kernel principal component analysis. Industrial and Engineering Chemistry Research, 2010, 49(17): 7849-7857
-
(2010)
Industrial and Engineering Chemistry Research
, vol.49
, Issue.17
, pp. 7849-7857
-
-
Alcala, C.F.1
Qin, S.J.2
-
5
-
-
63249084878
-
Improved kernel PCA-based monitoring approach for nonlinear processes
-
Ge Z Q, Yang C J, Song Z H. Improved kernel PCA-based monitoring approach for nonlinear processes. Chemical Engineering Science, 2009, 64(9): 2245-2255
-
(2009)
Chemical Engineering Science
, vol.64
, Issue.9
, pp. 2245-2255
-
-
Ge, Z.Q.1
Yang, C.J.2
Song, Z.H.3
-
6
-
-
0346911568
-
Nonlinear process monitoring using kernel principal component analysis
-
Lee J M, Yoo C K, Choi S W, Vanrolleghem P A, Lee I B. Nonlinear process monitoring using kernel principal component analysis. Chemical Engineering Science, 2004, 59(1): 223-234
-
(2004)
Chemical Engineering Science
, vol.59
, Issue.1
, pp. 223-234
-
-
Lee, J.M.1
Yoo, C.K.2
Choi, S.W.3
Vanrolleghem, P.A.4
Lee, I.B.5
-
7
-
-
0043015539
-
Nonlinear principal component analysis-based on principal curves and neural networks
-
Dong D, McAvoy T J. Nonlinear principal component analysis-based on principal curves and neural networks. Computers and Chemical Engineering, 1996, 20(1): 65-78
-
(1996)
Computers and Chemical Engineering
, vol.20
, Issue.1
, pp. 65-78
-
-
Dong, D.1
McAvoy, T.J.2
-
8
-
-
77749340024
-
Adaptive kernel principal component analysis (KPCA) for monitoring small disturbances of nonlinear processes
-
Cheng C Y, Hsu C C, Chen M C. Adaptive kernel principal component analysis (KPCA) for monitoring small disturbances of nonlinear processes. Industrial and Engineering Chemistry Research, 2010, 49(5): 2254-2262
-
(2010)
Industrial and Engineering Chemistry Research
, vol.49
, Issue.5
, pp. 2254-2262
-
-
Cheng, C.Y.1
Hsu, C.C.2
Chen, M.C.3
-
9
-
-
0037106519
-
Multivariate process monitoring and fault diagnosis by multi-scale PCA
-
Misra M, Yue H H, Qin S J, Ling C. Multivariate process monitoring and fault diagnosis by multi-scale PCA. Computers and Chemical Engineering, 2002, 26(9): 1281-1293
-
(2002)
Computers and Chemical Engineering
, vol.26
, Issue.9
, pp. 1281-1293
-
-
Misra, M.1
Yue, H.H.2
Qin, S.J.3
Ling, C.4
-
10
-
-
0032853906
-
Wavelets and nonlinear principal components analysis for process monitoring
-
Shao R, Jia F, Martin E B, Morris A J. Wavelets and nonlinear principal components analysis for process monitoring. Control Engineering Practice, 1999, 7(7): 865-879
-
(1999)
Control Engineering Practice
, vol.7
, Issue.7
, pp. 865-879
-
-
Shao, R.1
Jia, F.2
Martin, E.B.3
Morris, A.J.4
-
11
-
-
36749028738
-
Batch process monitoring in score space of two-dimensional dynamic principal component analysis (PCA)
-
Yao Y, Gao F R. Batch process monitoring in score space of two-dimensional dynamic principal component analysis (PCA). Industrial and Engineering Chemistry Research, 2007, 46(24): 8033-8043
-
(2007)
Industrial and Engineering Chemistry Research
, vol.46
, Issue.24
, pp. 8033-8043
-
-
Yao, Y.1
Gao, F.R.2
-
12
-
-
78049311275
-
Research on multistage-based MPCA modeling and monitoring method for batch processes
-
Chang Yu-Qing, Wang Shu, Tan Shuai, Wang Fu-Li, Yang Jie. Research on multistage-based MPCA modeling and monitoring method for batch processes. Acta Automatica Sinica, 2010, 36(9): 1312-1320
-
(2010)
Acta Automatica Sinica
, vol.36
, Issue.9
, pp. 1312-1320
-
-
Chang, Y.-Q.1
Wang, S.2
Tan, S.3
Wang, F.-L.4
Yang, J.5
-
13
-
-
78650021718
-
Fault detection of multi-mode process using segmented PCA based on differential transform
-
Tan Shuai, Wang Fu-Li, Chang Yu-Qing, Wang Shu, Zhou He. Fault detection of multi-mode process using segmented PCA based on differential transform. Acta Automatica Sinica, 2010, 36(11): 1626-1635
-
(2010)
Acta Automatica Sinica
, vol.36
, Issue.11
, pp. 1626-1635
-
-
Tan, S.1
Wang, F.-L.2
Chang, Y.-Q.3
Wang, S.4
Zhou, H.5
-
14
-
-
0000736392
-
Analysis of multi-block and hierarchical PCA and PLS models
-
Westerhuis J A, Kourti T, Macgregor J F. Analysis of multi-block and hierarchical PCA and PLS models. Journal of Chemometrics, 1998, 12(5): 301-321
-
(1998)
Journal of Chemometrics
, vol.12
, Issue.5
, pp. 301-321
-
-
Westerhuis, J.A.1
Kourti, T.2
Macgregor, J.F.3
-
15
-
-
77952682127
-
Decentralized fault diagnosis of large-scale processes using multiblock kernel principal component analysis
-
Zhang Y W, Zhou H, Qin S J. Decentralized fault diagnosis of large-scale processes using multiblock kernel principal component analysis. Acta Automatica Sinica, 2010, 36(4): 593-597
-
(2010)
Acta Automatica Sinica
, vol.36
, Issue.4
, pp. 593-597
-
-
Zhang, Y.W.1
Zhou, H.2
Qin, S.J.3
-
16
-
-
0042826822
-
Independent component analysis: Algorithms and applications
-
Hyvärinen A, Oja E. Independent component analysis: algorithms and applications. Neural Networks, 2000, 13(4-5): 411-430
-
(2000)
Neural Networks
, vol.13
, Issue.4-5
, pp. 411-430
-
-
Hyvärinen, A.1
Oja, E.2
-
17
-
-
0141496923
-
Independent component analysis: A survey
-
Yang Zhu-Qing, Li Yong, Hu De-Wen. Independent component analysis: a survey. Acta Automatica Sinica, 2002, 28(5): 762-772
-
(2002)
Acta Automatica Sinica
, vol.28
, Issue.5
, pp. 762-772
-
-
Yang, Z.-Q.1
Li, Y.2
Hu, D.-W.3
-
18
-
-
49149092020
-
Batch process monitoring based on multilevel ICA-PCA
-
Ge Z Q, Song Z H. Batch process monitoring based on multilevel ICA-PCA. Journal of Zhejiang University Science A, 2008, 9(8): 1061-1069
-
(2008)
Journal of Zhejiang University Science A
, vol.9
, Issue.8
, pp. 1061-1069
-
-
Ge, Z.Q.1
Song, Z.H.2
-
19
-
-
53349175658
-
Fault detection and diagnosis of nonlinear processes using improved kernel independent component analysis (KICA) and support vector machine (SVM)
-
Zhang Y W. Fault detection and diagnosis of nonlinear processes using improved kernel independent component analysis (KICA) and support vector machine (SVM). Industrial and Engineering Chemistry Research, 2008, 47(18): 6961-6971
-
(2008)
Industrial and Engineering Chemistry Research
, vol.47
, Issue.18
, pp. 6961-6971
-
-
Zhang, Y.W.1
-
20
-
-
1342285571
-
Statistical process monitoring with independent component analysis
-
Lee J M, Yoo C K, Lee I B. Statistical process monitoring with independent component analysis. Journal of Process Control, 2004, 14(5): 467-485
-
(2004)
Journal of Process Control
, vol.14
, Issue.5
, pp. 467-485
-
-
Lee, J.M.1
Yoo, C.K.2
Lee, I.B.3
-
21
-
-
0035802262
-
Reconstruction-based fault identification using a combined index
-
Yue H H, Qin S J. Reconstruction-based fault identification using a combined index. Industrial and Engineering Chemistry Research, 2001, 40(20): 4403-4414
-
(2001)
Industrial and Engineering Chemistry Research
, vol.40
, Issue.20
, pp. 4403-4414
-
-
Yue, H.H.1
Qin, S.J.2
-
22
-
-
0030525683
-
Non-parametric confidence bounds for process performance monitoring charts
-
Martin E B, Morris A J. Non-parametric confidence bounds for process performance monitoring charts. Journal of Process Control, 1996, 6(6): 349-358
-
(1996)
Journal of Process Control
, vol.6
, Issue.6
, pp. 349-358
-
-
Martin, E.B.1
Morris, A.J.2
-
23
-
-
0028892168
-
Disturbance detection and isolation by dynamic principal component analysis
-
Ku W F, Storer R H, Georgakis C. Disturbance detection and isolation by dynamic principal component analysis. Chemometrics and Intelligent Laboratory Systems, 1995, 30(1): 179-196
-
(1995)
Chemometrics and Intelligent Laboratory Systems
, vol.30
, Issue.1
, pp. 179-196
-
-
Ku, W.F.1
Storer, R.H.2
Georgakis, C.3
|