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Volumn 18, Issue 4, 2008, Pages 429-442

Fault detection and isolation with robust principal component analysis

Author keywords

Fault detection and isolation; Outliers; Principal component analysis; Robustness; Structured residual vector; Variable reconstruction

Indexed keywords

COVARIANCE MATRIX; FAULT DETECTION; PHOTOMASKS; REPAIR; RESTORATION; ROBUST CONTROL; VECTORS;

EID: 58149184003     PISSN: 1641876X     EISSN: None     Source Type: Journal    
DOI: 10.2478/v10006-008-0038-3     Document Type: Article
Times cited : (100)

References (16)
  • 3
    • 18744376591 scopus 로고    scopus 로고
    • High breakdown estimators for principal components: The projectionpursuit approach revisited
    • Croux C. and Ruiz-Gazen A. (2005). High breakdown estimators for principal components: The projectionpursuit approach revisited, Journal of Multivariate Analysis 95(1): 206-226.
    • (2005) Journal of Multivariate Analysis , vol.95 , Issue.1 , pp. 206-226
    • Croux, C.1    Ruiz-Gazen, A.2
  • 4
    • 0032144398 scopus 로고    scopus 로고
    • A subspace approach to multidimensional fault identification and reconstruction
    • Dunia R. and Qin S. (1998). A subspace approach to multidimensional fault identification and reconstruction, American Institute of Chemical Engineers Journal 44 (8): 1813-1831.
    • (1998) American Institute of Chemical Engineers Journal , vol.44 , Issue.8 , pp. 1813-1831
    • Dunia, R.1    Qin, S.2
  • 5
    • 33645402336 scopus 로고    scopus 로고
    • An improved PCA scheme for sensor FDI: Application to an air quality monitoring network
    • Harkat M.-F., Mourot G. and Ragot J. (2006). An improved PCA scheme for sensor FDI: Application to an air quality monitoring network, Journal of Process Control 16(6): 625-634.
    • (2006) Journal of Process Control , vol.16 , Issue.6 , pp. 625-634
    • Harkat, M.-F.1    Mourot, G.2    Ragot, J.3
  • 6
    • 13444287831 scopus 로고    scopus 로고
    • RobPCA: A new approach to robust principal component analysis
    • Hubert M., Rousseeuw P. and Van den Branden, K. (2005). RobPCA: A new approach to robust principal component analysis, Technometrics 47 (1): 64-79.
    • (2005) Technometrics , vol.47 , Issue.1 , pp. 64-79
    • Hubert, M.1    Rousseeuw, P.2    Van den Branden, K.3
  • 7
  • 8
    • 0018503842 scopus 로고
    • Control procedures for residuals associated with principal component analysis
    • Jackson J. and Mudholkar G. S. (1979). Control procedures for residuals associated with principal component analysis, Technometrics 21(3): 341-349.
    • (1979) Technometrics , vol.21 , Issue.3 , pp. 341-349
    • Jackson, J.1    Mudholkar, G.S.2
  • 9
    • 35548968908 scopus 로고    scopus 로고
    • Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry
    • 1.-2
    • Kano M. and Nakagawa Y. (2008). Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry, Computers & Chemical Engineering 32(1.-2): 12-24.
    • (2008) Computers & Chemical Engineering , vol.32 , pp. 12-24
    • Kano, M.1    Nakagawa, Y.2
  • 10
    • 0001337027 scopus 로고
    • Projection-pursuit approach to robust dispersion matrices and principal components: Primary theory and Monte Carlo
    • Li G. and Chen Z. (1985). Projection-pursuit approach to robust dispersion matrices and principal components: Primary theory and Monte Carlo, Journal of the American Statistical Association 80(391): 759-766.
    • (1985) Journal of the American Statistical Association , vol.80 , Issue.391 , pp. 759-766
    • Li, G.1    Chen, Z.2
  • 11
    • 0035546347 scopus 로고    scopus 로고
    • Consistent dynamic PCA based on errors-in-variables subspace identification
    • Li W. and Qin S. J. (2001). Consistent dynamic PCA based on errors-in-variables subspace identification, Journal of Process Control 11(6): 661-678.
    • (2001) Journal of Process Control , vol.11 , Issue.6 , pp. 661-678
    • Li, W.1    Qin, S.J.2
  • 12
    • 58149199786 scopus 로고    scopus 로고
    • Robust Statistics: Theory and Methods, Wiley, New York, NY. Qin S. J. (2003). Statistical process monitoring: Basics and beyond
    • Maronna R. A., Martin R. and Yohai V. J. (2006). Robust Statistics: Theory and Methods, Wiley, New York, NY. Qin S. J. (2003). Statistical process monitoring: Basics and beyond, Journal of Chemometrics 17(8-9):480-502.
    • (2006) Journal of Chemometrics , vol.17 , Issue.8-9 , pp. 480-502
    • Maronna, R.A.1    Martin, R.2    Yohai, V.J.3
  • 14
    • 0032680362 scopus 로고    scopus 로고
    • Fast algorithm for the minimum covariance determinant estimator
    • Rousseeuw P. and Van Driessen K. (1999). Fast algorithm for the minimum covariance determinant estimator, Technometrics 41(3): 212-223.
    • (1999) Technometrics , vol.41 , Issue.3 , pp. 212-223
    • Rousseeuw, P.1    Van Driessen, K.2
  • 15
    • 0001809110 scopus 로고    scopus 로고
    • A very simple robust estimator of a dispersion matrix
    • Ruiz-Gazen, A. (1996). A very simple robust estimator of a dispersion matrix, Computational Statistics and Data Analysis 21(2): 149-162.
    • (1996) Computational Statistics and Data Analysis , vol.21 , Issue.2 , pp. 149-162
    • Ruiz-Gazen, A.1
  • 16
    • 0035802262 scopus 로고    scopus 로고
    • Reconstruction-based fault identification using a combined index
    • Yue, H. and Qin, S. (2001). Reconstruction-based fault identification using a combined index. Industrial and Engineering Chemistry Research 40(20): 4403-4414.
    • (2001) Industrial and Engineering Chemistry Research , vol.40 , Issue.20 , pp. 4403-4414
    • Yue, H.1    Qin, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.