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Volumn 119, Issue , 2012, Pages 11-20

Chemical processes monitoring based on weighted principal component analysis and its application

Author keywords

Chemical process monitoring; Fault detection; Fault diagnosis; Weighted principal component

Indexed keywords

ANALYTIC METHOD; ARTICLE; CHEMICAL REACTION; INFORMATION PROCESSING; ONLINE MONITORING; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROCESS MODEL; PROCESS MONITORING; STATISTICAL ANALYSIS; STATISTICAL MODEL; WEIGHTED PRINCIPAL COMPONENT ANALYSIS;

EID: 84867006916     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2012.09.002     Document Type: Article
Times cited : (50)

References (34)
  • 1
    • 0034643075 scopus 로고    scopus 로고
    • Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis
    • Chiang L.H., Russell E.L., Braatz R.D. Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis. Chemometrics and Intelligent Laboratory Systems 2000, 50:243-252.
    • (2000) Chemometrics and Intelligent Laboratory Systems , vol.50 , pp. 243-252
    • Chiang, L.H.1    Russell, E.L.2    Braatz, R.D.3
  • 3
    • 54949117106 scopus 로고    scopus 로고
    • Diagnosis of process faults in chemical systems using a local partial least squares approach
    • Kruger U., Dimitriadis G. Diagnosis of process faults in chemical systems using a local partial least squares approach. AICHE Journal 2008, 54:2581-2596.
    • (2008) AICHE Journal , vol.54 , pp. 2581-2596
    • Kruger, U.1    Dimitriadis, G.2
  • 4
    • 1342285571 scopus 로고    scopus 로고
    • 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, 14:467-485.
    • (2004) Journal of Process Control , vol.14 , pp. 467-485
    • Lee, J.M.1    Yoo, C.K.2    Lee, I.B.3
  • 5
    • 0242354134 scopus 로고    scopus 로고
    • Statistical process monitoring: basics and beyond
    • Qin S.J. Statistical process monitoring: basics and beyond. Journal of Chemometrics 2003, 17:480-502.
    • (2003) Journal of Chemometrics , vol.17 , pp. 480-502
    • Qin, S.J.1
  • 6
    • 0034621334 scopus 로고    scopus 로고
    • Fault detection in industrial processes using canonical variate analysis and dynamic principal component analysis
    • Russell E.L., Chiang L.H., Braatz R.D. Fault detection in industrial processes using canonical variate analysis and dynamic principal component analysis. Chemometrics and Intelligent Laboratory Systems 2000, 51:81-93.
    • (2000) Chemometrics and Intelligent Laboratory Systems , vol.51 , pp. 81-93
    • Russell, E.L.1    Chiang, L.H.2    Braatz, R.D.3
  • 7
    • 33845623677 scopus 로고    scopus 로고
    • Application of nonlinear feature extraction and support vector machines for fault diagnosis of induction motors
    • Widodo A., Yang B.S. Application of nonlinear feature extraction and support vector machines for fault diagnosis of induction motors. Expert Systems with Applications 2007, 33:241-250.
    • (2007) Expert Systems with Applications , vol.33 , pp. 241-250
    • Widodo, A.1    Yang, B.S.2
  • 8
    • 0034334827 scopus 로고    scopus 로고
    • Non-linear principal components analysis with application to process fault detection
    • Jia F., Martin E., Morris A. Non-linear principal components analysis with application to process fault detection. International Journal of Systems Science 2000, 31:1473-1487.
    • (2000) International Journal of Systems Science , vol.31 , pp. 1473-1487
    • Jia, F.1    Martin, E.2    Morris, A.3
  • 10
    • 77957298441 scopus 로고    scopus 로고
    • Fault detection based on Kernel Principal Component Analysis
    • Nguyen V.H., Golinval J.C. Fault detection based on Kernel Principal Component Analysis. Engineering Structures 2010, 32:3683-3691.
    • (2010) Engineering Structures , vol.32 , pp. 3683-3691
    • Nguyen, V.H.1    Golinval, J.C.2
  • 11
    • 10044259622 scopus 로고    scopus 로고
    • Nonlinear dynamic process monitoring based on dynamic kernel PCA
    • Choi S.W., Lee I.B. Nonlinear dynamic process monitoring based on dynamic kernel PCA. Chemical Engineering Science 2004, 59:5897-5908.
    • (2004) Chemical Engineering Science , vol.59 , pp. 5897-5908
    • Choi, S.W.1    Lee, I.B.2
  • 13
    • 0034651054 scopus 로고    scopus 로고
    • Statistical monitoring and diagnosis of automatic controlled processes using dynamic PCA
    • Tsung F. Statistical monitoring and diagnosis of automatic controlled processes using dynamic PCA. International Journal of Production Research 2000, 38:625-637.
    • (2000) International Journal of Production Research , vol.38 , pp. 625-637
    • Tsung, F.1
  • 14
    • 77953121551 scopus 로고    scopus 로고
    • Maximum-likelihood mixture factor analysis model and its application for process monitoring
    • Ge Z.Q., Song Z.H. Maximum-likelihood mixture factor analysis model and its application for process monitoring. Chemometrics and Intelligent Laboratory Systems 2010, 102:53-61.
    • (2010) Chemometrics and Intelligent Laboratory Systems , vol.102 , pp. 53-61
    • Ge, Z.Q.1    Song, Z.H.2
  • 15
    • 78449282926 scopus 로고    scopus 로고
    • Kernel generalization of PPCA for nonlinear probabilistic monitoring
    • Ge Z.Q., Song Z.H. Kernel generalization of PPCA for nonlinear probabilistic monitoring. Industrial and Engineering Chemistry Research 2010, 49:11832-11836.
    • (2010) Industrial and Engineering Chemistry Research , vol.49 , pp. 11832-11836
    • Ge, Z.Q.1    Song, Z.H.2
  • 17
    • 2442495227 scopus 로고    scopus 로고
    • Fault detection of batch processes using multiway kernel principal component analysis
    • Lee J.M., Yoo C., Lee I.B. Fault detection of batch processes using multiway kernel principal component analysis. Computers and Chemical Engineering 2004, 28:1837-1847.
    • (2004) Computers and Chemical Engineering , vol.28 , pp. 1837-1847
    • Lee, J.M.1    Yoo, C.2    Lee, I.B.3
  • 18
    • 0028483476 scopus 로고
    • Monitoring batch processes using multiway principal component analysis
    • Nomikos P., MacGregor J.F. Monitoring batch processes using multiway principal component analysis. AICHE Journal 1994, 40:1361-1375.
    • (1994) AICHE Journal , vol.40 , pp. 1361-1375
    • Nomikos, P.1    MacGregor, J.F.2
  • 21
    • 0030262558 scopus 로고    scopus 로고
    • Multivariate SPC methods for process and product monitoring
    • Kourti T., MacGregor J.F. Multivariate SPC methods for process and product monitoring. Journal of Quality Technology 1996, 28:409-428.
    • (1996) Journal of Quality Technology , vol.28 , pp. 409-428
    • Kourti, T.1    MacGregor, J.F.2
  • 24
    • 0028354319 scopus 로고
    • Exponentially weighted moving principal components analysis and projections to latent structures
    • Wold S. Exponentially weighted moving principal components analysis and projections to latent structures. Chemometrics and Intelligent Laboratory Systems 1994, 23:149-161.
    • (1994) Chemometrics and Intelligent Laboratory Systems , vol.23 , pp. 149-161
    • Wold, S.1
  • 26
    • 70349338494 scopus 로고    scopus 로고
    • Multilevel simultaneous component analysis for fault detection in multicampaign process monitoring: application to on-line high performance liquid chromatography of a continuous process
    • Ferreira D.L.S., Kittiwachana S., Fido L.A., Thompson D.R., Escott R.E.A., Brereton R.G. Multilevel simultaneous component analysis for fault detection in multicampaign process monitoring: application to on-line high performance liquid chromatography of a continuous process. Analyst 2009, 134:1571-1585.
    • (2009) Analyst , vol.134 , pp. 1571-1585
    • Ferreira, D.L.S.1    Kittiwachana, S.2    Fido, L.A.3    Thompson, D.R.4    Escott, R.E.A.5    Brereton, R.G.6
  • 27
    • 84863101603 scopus 로고
    • Quality control methods for several related variables
    • Jackson J.E. Quality control methods for several related variables. Technometrics 1959, 1:359-377.
    • (1959) Technometrics , vol.1 , pp. 359-377
    • Jackson, J.E.1
  • 28
    • 0018503842 scopus 로고
    • Control procedures for residuals associated with principal component analysis
    • Jackson J.E., Mudholkar G.S. Control procedures for residuals associated with principal component analysis. Technometrics 1979, 21:341-349.
    • (1979) Technometrics , vol.21 , pp. 341-349
    • Jackson, J.E.1    Mudholkar, G.S.2
  • 33
    • 0028431355 scopus 로고
    • Base control for the Tennessee Eastman problem
    • McAvoy T., Ye N. Base control for the Tennessee Eastman problem. Computers and Chemical Engineering 1994, 18:383-413.
    • (1994) Computers and Chemical Engineering , vol.18 , pp. 383-413
    • McAvoy, T.1    Ye, N.2


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