메뉴 건너뛰기




Volumn 96, Issue 2, 2009, Pages 132-143

Moving window kernel PCA for adaptive monitoring of nonlinear processes

Author keywords

Adaptive; Kernel PCA; Moving window; Multivariate statistical process control; Nonlinear process; Numerically efficient

Indexed keywords

ADAPTATION; ALGORITHM; ARTICLE; COVARIANCE; DECOMPOSITION; DISTILLATION; KERNEL METHOD; MEMORY; MONITORING; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SIMULATION;

EID: 64249101035     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chemolab.2009.01.002     Document Type: Article
Times cited : (193)

References (47)
  • 1
    • 36749052831 scopus 로고    scopus 로고
    • Monitoring a complex refining process using multivariate statistics
    • AlGhazzawi A., and Lennox B. Monitoring a complex refining process using multivariate statistics. Control Engineering Practice 16 3 (2008) 294-307
    • (2008) Control Engineering Practice , vol.16 , Issue.3 , pp. 294-307
    • AlGhazzawi, A.1    Lennox, B.2
  • 4
    • 84937549955 scopus 로고
    • The scree test for the number of factors
    • Cattell R.B. The scree test for the number of factors. Multivariate Behavioral Research 1 2 (1966) 245-276
    • (1966) Multivariate Behavioral Research , vol.1 , Issue.2 , pp. 245-276
    • Cattell, R.B.1
  • 6
    • 10244238854 scopus 로고    scopus 로고
    • Fault identification for process monitoring using kernel principal component analysis
    • Choi J.-H., Lee J.-M., Choi S.W., Lee D., and Lee I.-B. Fault identification for process monitoring using kernel principal component analysis. Chemical Engineering Science 60 1 (2005) 279-288
    • (2005) Chemical Engineering Science , vol.60 , Issue.1 , pp. 279-288
    • Choi, J.-H.1    Lee, J.-M.2    Choi, S.W.3    Lee, D.4    Lee, I.-B.5
  • 8
    • 36148959019 scopus 로고    scopus 로고
    • Improved kernel principal component analysis for fault detection
    • Cui P., Li J., and Wang G. Improved kernel principal component analysis for fault detection. Expert Systems With Applications 34 2 (2008) 1210-1219
    • (2008) Expert Systems With Applications , vol.34 , Issue.2 , pp. 1210-1219
    • Cui, P.1    Li, J.2    Wang, G.3
  • 9
    • 0043015539 scopus 로고    scopus 로고
    • Nonlinear principal component analysis-based on principal curves and neural networks
    • Dong D., and McAvoy T.J. Nonlinear principal component analysis-based on principal curves and neural networks. Computers and Chemical Engineering 20 1 (1996) 65-78
    • (1996) Computers and Chemical Engineering , vol.20 , Issue.1 , pp. 65-78
    • Dong, D.1    McAvoy, T.J.2
  • 10
    • 34247109083 scopus 로고    scopus 로고
    • Process monitoring based on independent component analysis-principal component analysis (ica-pca) and similarity factors
    • Ge Z., and Song Z. Process monitoring based on independent component analysis-principal component analysis (ica-pca) and similarity factors. Industrial & Engineering Chemistry Research 46 7 (2007) 2054-2063
    • (2007) Industrial & Engineering Chemistry Research , vol.46 , Issue.7 , pp. 2054-2063
    • Ge, Z.1    Song, Z.2
  • 11
    • 0001070999 scopus 로고
    • Some modified matrix eigenvalue problems
    • Golub G.H. Some modified matrix eigenvalue problems. SIAM Review 15 2 (1973) 318-334
    • (1973) SIAM Review , vol.15 , Issue.2 , pp. 318-334
    • Golub, G.H.1
  • 15
    • 0036903144 scopus 로고    scopus 로고
    • Adding and subtracting eigenspaces with eigenvalue decomposition and singular value decomposition
    • Hall P., Marshall D., and Martin R. Adding and subtracting eigenspaces with eigenvalue decomposition and singular value decomposition. Image and Vision Computing 20 13-14 (2002) 1009-1016
    • (2002) Image and Vision Computing , vol.20 , Issue.13-14 , pp. 1009-1016
    • Hall, P.1    Marshall, D.2    Martin, R.3
  • 16
    • 33846798101 scopus 로고    scopus 로고
    • Subspace-based gearbox condition monitoring by kernel principal component analysis
    • He Q., Kong F., and Yan R. Subspace-based gearbox condition monitoring by kernel principal component analysis. Mechanical Systems and Signal Processing 21 4 (2007) 1755-1772
    • (2007) Mechanical Systems and Signal Processing , vol.21 , Issue.4 , pp. 1755-1772
    • He, Q.1    Kong, F.2    Yan, R.3
  • 19
    • 0034334827 scopus 로고    scopus 로고
    • Nonlinear principal components analysis with application to process fault detection
    • Jia F., Martin E.B., and Morris A.J. Nonlinear principal components analysis with application to process fault detection. International Journal of Systems Science 31 11 (2000) 1473-1487
    • (2000) International Journal of Systems Science , vol.31 , Issue.11 , pp. 1473-1487
    • Jia, F.1    Martin, E.B.2    Morris, A.J.3
  • 22
    • 0026113980 scopus 로고
    • Nonlinear principal component analysis using autoassociative neural networks
    • Kramer M.A. Nonlinear principal component analysis using autoassociative neural networks. AIChE journal 37 3 (1991) 233-243
    • (1991) AIChE journal , vol.37 , Issue.3 , pp. 233-243
    • Kramer, M.A.1
  • 24
    • 0035442469 scopus 로고    scopus 로고
    • Extended pls approach for enhanced condition monitoring of industrial processes
    • Kruger U., Chen Q., Sandoz D.J., and McFarlane R.C. Extended pls approach for enhanced condition monitoring of industrial processes. AIChE Journal 47 9 (2001) 2076-2091
    • (2001) AIChE Journal , vol.47 , Issue.9 , pp. 2076-2091
    • Kruger, U.1    Chen, Q.2    Sandoz, D.J.3    McFarlane, R.C.4
  • 25
    • 64249158480 scopus 로고    scopus 로고
    • U. Kruger, J. Zhang, L. Xie, 2007. Principal manifolds for data visualization and dimension reduction. 58 of Lecture notes in computational science and engineering. Springer Verlag, Berlin-Heidelberg-New York, Ch. Developments and applications of nonlinear principal component analysis - A review, pp. 1-44.
    • U. Kruger, J. Zhang, L. Xie, 2007. Principal manifolds for data visualization and dimension reduction. Vol. 58 of Lecture notes in computational science and engineering. Springer Verlag, Berlin-Heidelberg-New York, Ch. Developments and applications of nonlinear principal component analysis - A review, pp. 1-44.
  • 26
    • 33745673605 scopus 로고    scopus 로고
    • Multivariate online monitoring of a full-scale biological anaerobic filter process using kernel-based algorithms
    • Lee D.S., Lee M.W., Woo S.H., Kim Y.-J., and Park J.M. Multivariate online monitoring of a full-scale biological anaerobic filter process using kernel-based algorithms. Industrial & Engineering Chemistry Research 45 12 (2006) 4335-4344
    • (2006) Industrial & Engineering Chemistry Research , vol.45 , Issue.12 , pp. 4335-4344
    • Lee, D.S.1    Lee, M.W.2    Woo, S.H.3    Kim, Y.-J.4    Park, J.M.5
  • 27
    • 33749473097 scopus 로고    scopus 로고
    • Fault detection and diagnosis based on modified independent component analysis
    • Lee J.M., Qin S.J., and Lee I.B. Fault detection and diagnosis based on modified independent component analysis. AIChE Journal 52 10 (2006) 3501-3514
    • (2006) AIChE Journal , vol.52 , Issue.10 , pp. 3501-3514
    • Lee, J.M.1    Qin, S.J.2    Lee, I.B.3
  • 30
    • 52649119206 scopus 로고    scopus 로고
    • Statistical-based monitoring of multivariate non-Gaussian systems
    • Liu X., Xie L., Kruger U., Littler T., and Wang S. Statistical-based monitoring of multivariate non-Gaussian systems. AIChE Journal 54 9 (2008) 2379-2391
    • (2008) AIChE Journal , vol.54 , Issue.9 , pp. 2379-2391
    • Liu, X.1    Xie, L.2    Kruger, U.3    Littler, T.4    Wang, S.5
  • 32
    • 0001620483 scopus 로고    scopus 로고
    • Multivariate statistical process control; example from the chemical process industry
    • Morud T.E. Multivariate statistical process control; example from the chemical process industry. Journal of Chemometrics 10 5-6 (1996) 669-675
    • (1996) Journal of Chemometrics , vol.10 , Issue.5-6 , pp. 669-675
    • Morud, T.E.1
  • 33
    • 0029252734 scopus 로고
    • Multivariate spc charts for monitoring batch processes
    • Nomikos P., and MacGregor J.F. Multivariate spc charts for monitoring batch processes. Technometrics 37 1 (1995) 41-59
    • (1995) Technometrics , vol.37 , Issue.1 , pp. 41-59
    • Nomikos, P.1    MacGregor, J.F.2
  • 34
    • 0001288470 scopus 로고
    • Accuracy and effectiveness of the Lanczos algorithm
    • Paige C.C. Accuracy and effectiveness of the Lanczos algorithm. Linear Algebra and Its Applications 34 (1980) 235-258
    • (1980) Linear Algebra and Its Applications , vol.34 , pp. 235-258
    • Paige, C.C.1
  • 36
    • 0033903077 scopus 로고    scopus 로고
    • Determining the number of principal components for best reconstruction
    • Qin S.J., and Dunia R. Determining the number of principal components for best reconstruction. Journal of Process Control 10 2 (2000) 245-250
    • (2000) Journal of Process Control , vol.10 , Issue.2 , pp. 245-250
    • Qin, S.J.1    Dunia, R.2
  • 38
    • 0029322882 scopus 로고
    • Reducing data dimensionality through optimizing neural network inputs
    • Tan S., and Mavrovouniotis M.L. Reducing data dimensionality through optimizing neural network inputs. AIChE Journal 41 6 (1995) 1471-1480
    • (1995) AIChE Journal , vol.41 , Issue.6 , pp. 1471-1480
    • Tan, S.1    Mavrovouniotis, M.L.2
  • 39
    • 0001925804 scopus 로고
    • Multivariate control charts for individual observations
    • Tracy N.D., Young J.C., and Mason R.L. Multivariate control charts for individual observations. Journal of Quality Control 24 2 (1992) 88-95
    • (1992) Journal of Quality Control , vol.24 , Issue.2 , pp. 88-95
    • Tracy, N.D.1    Young, J.C.2    Mason, R.L.3
  • 40
    • 0033230994 scopus 로고    scopus 로고
    • Selection of the number of principal components: the variance of the reconstruction error criterion compared to other methods
    • Valle S., Li W.H., and Qin S.J. Selection of the number of principal components: the variance of the reconstruction error criterion compared to other methods. Industrial & Engineering Chemistry Research 38 11 (1999) 4389-4401
    • (1999) Industrial & Engineering Chemistry Research , vol.38 , Issue.11 , pp. 4389-4401
    • Valle, S.1    Li, W.H.2    Qin, S.J.3
  • 43
    • 0038198780 scopus 로고    scopus 로고
    • Recursive partial least squares algorithms for monitoring complex industrial processes
    • Wang X., Kruger U., and Lennox B. Recursive partial least squares algorithms for monitoring complex industrial processes. Control Engineering Practice 11 6 (2003) 613-632
    • (2003) Control Engineering Practice , vol.11 , Issue.6 , pp. 613-632
    • Wang, X.1    Kruger, U.2    Lennox, B.3
  • 44
    • 34547371609 scopus 로고    scopus 로고
    • Recursive kernel pca and its application in adaptive monitoring of nonlinear processes
    • Xie L., and Wang S.Q. Recursive kernel pca and its application in adaptive monitoring of nonlinear processes. Journal of Chemical Industry and Engineering 58 7 (2007) 1776-1782
    • (2007) Journal of Chemical Industry and Engineering , vol.58 , Issue.7 , pp. 1776-1782
    • Xie, L.1    Wang, S.Q.2
  • 45
    • 33747316325 scopus 로고    scopus 로고
    • Nonlinear multivariate filtering and bioprocess monitoring for supervising nonlinear biological processes
    • Yoo C.K., and Lee I.B. Nonlinear multivariate filtering and bioprocess monitoring for supervising nonlinear biological processes. Process Biochemistry 41 8 (2006) 1854-1863
    • (2006) Process Biochemistry , vol.41 , Issue.8 , pp. 1854-1863
    • Yoo, C.K.1    Lee, I.B.2
  • 46
    • 33646178973 scopus 로고    scopus 로고
    • Performance monitoring of processes with multiple operating modes through multiple pls models
    • Zhang J., Zhao S.J., and Xu Y.M. Performance monitoring of processes with multiple operating modes through multiple pls models. Journal of Process Control 16 7 (2006) 763-772
    • (2006) Journal of Process Control , vol.16 , Issue.7 , pp. 763-772
    • Zhang, J.1    Zhao, S.J.2    Xu, Y.M.3
  • 47
    • 35148823629 scopus 로고    scopus 로고
    • Stage-based soft-transition multiple pca modeling and on-line monitoring strategy for batch processes
    • Zhao C., Wang F., Lu N., and Jia M. Stage-based soft-transition multiple pca modeling and on-line monitoring strategy for batch processes. Journal of Process Control 17 9 (2007) 728-741
    • (2007) Journal of Process Control , vol.17 , Issue.9 , pp. 728-741
    • Zhao, C.1    Wang, F.2    Lu, N.3    Jia, M.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.