메뉴 건너뛰기




Volumn 36, Issue 2 PART 1, 2009, Pages 1423-1432

Improved kernel fisher discriminant analysis for fault diagnosis

Author keywords

Fault diagnosis; Feature vector selection (FVS); Kernel fisher discriminant analysis (KFDA); Nearest feature line (NFL)

Indexed keywords

DISCRIMINANT ANALYSIS; FAILURE ANALYSIS; FEATURE EXTRACTION; FISHER INFORMATION MATRIX; LEARNING ALGORITHMS;

EID: 56349114104     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.11.043     Document Type: Article
Times cited : (56)

References (32)
  • 1
    • 0034861805 scopus 로고    scopus 로고
    • Baudat, G., & Anouar, F. (2001). Kernel-based methods and function approximation. In Proceedings of International Conference on Neural Networks (pp. 1244-1249). Washington, DC.
    • Baudat, G., & Anouar, F. (2001). Kernel-based methods and function approximation. In Proceedings of International Conference on Neural Networks (pp. 1244-1249). Washington, DC.
  • 2
    • 0034296402 scopus 로고    scopus 로고
    • Generalized discriminant analysis using a kernel approach
    • Baudat G., and Anouar F. Generalized discriminant analysis using a kernel approach. Neural Computation 12 (2000) 2385-2404
    • (2000) Neural Computation , vol.12 , pp. 2385-2404
    • Baudat, G.1    Anouar, F.2
  • 3
    • 0037110983 scopus 로고    scopus 로고
    • Modular simulation package for fed-batch fermentation: Penicillin production
    • Birol G., Ündey C., and Cinar A.A. Modular simulation package for fed-batch fermentation: Penicillin production. Computers and Chemical Engineering 26 (2002) 1553-1565
    • (2002) Computers and Chemical Engineering , vol.26 , pp. 1553-1565
    • Birol, G.1    Ündey, C.2    Cinar, A.A.3
  • 4
    • 33644990573 scopus 로고    scopus 로고
    • On-line batch process monitoring using MHMT-based MPCA
    • Chen J.H., and Chen H.H. On-line batch process monitoring using MHMT-based MPCA. Chemical Engineering Science 61 (2006) 3223-3239
    • (2006) Chemical Engineering Science , vol.61 , pp. 3223-3239
    • Chen, J.H.1    Chen, H.H.2
  • 6
    • 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., and 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 50 (2000) 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
  • 7
    • 36148963325 scopus 로고    scopus 로고
    • An orthogonally filtered tree classifier based on nonlinear kernel-based optimal representation of data
    • Cho H.W. An orthogonally filtered tree classifier based on nonlinear kernel-based optimal representation of data. Expert Systems with Applications 34 2 (2008) 1028-1037
    • (2008) Expert Systems with Applications , vol.34 , Issue.2 , pp. 1028-1037
    • Cho, H.W.1
  • 8
    • 33750429920 scopus 로고    scopus 로고
    • Nonlinear feature extraction and classification of multivariate process data in kernel feature space
    • Cho H.W. Nonlinear feature extraction and classification of multivariate process data in kernel feature space. Expert Systems with Applications 32 (2007) 534-542
    • (2007) Expert Systems with Applications , vol.32 , pp. 534-542
    • Cho, H.W.1
  • 9
    • 33846432352 scopus 로고    scopus 로고
    • Identification of contributing variables using kernel-based discriminant modeling and reconstruction
    • Cho H.W. Identification of contributing variables using kernel-based discriminant modeling and reconstruction. Expert Systems with Applications 33 (2007) 274-285
    • (2007) Expert Systems with Applications , vol.33 , pp. 274-285
    • Cho, H.W.1
  • 10
    • 10044259622 scopus 로고    scopus 로고
    • Nonlinear dynamic process monitoring based on dynamic KPCA
    • Choi S.W., and Lee I.B. Nonlinear dynamic process monitoring based on dynamic KPCA. Chemical Engineering Science 59 (2004) 5897-5908
    • (2004) Chemical Engineering Science , vol.59 , pp. 5897-5908
    • Choi, S.W.1    Lee, I.B.2
  • 12
  • 13
    • 10244238854 scopus 로고    scopus 로고
    • Fault identification for process monitoring using kernel principal component analysis
    • Cho 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 (2005) 279-288
    • (2005) Chemical Engineering Science , vol.60 , pp. 279-288
    • Cho, J.H.1    Lee, J.M.2    Choi, S.W.3    Lee, D.4    Lee, I.B.5
  • 15
    • 36148959019 scopus 로고    scopus 로고
    • Improved kernel principal component analysis for fault detection
    • Cui P.L., Li J.H., and Wang G.Z. Improved kernel principal component analysis for fault detection. Expert Systems with Applications 34 2 (2007) 1210-1219
    • (2007) Expert Systems with Applications , vol.34 , Issue.2 , pp. 1210-1219
    • Cui, P.L.1    Li, J.H.2    Wang, G.Z.3
  • 18
    • 9744237208 scopus 로고    scopus 로고
    • Multiple-fault diagnosis of the Tennessee Eastman process based on system decomposition and dynamic PLS
    • Lee G., Han C.H., and Yoon E.S. Multiple-fault diagnosis of the Tennessee Eastman process based on system decomposition and dynamic PLS. Industrial & Engineering Chemistry Research 43 (2004) 8037-8048
    • (2004) Industrial & Engineering Chemistry Research , vol.43 , pp. 8037-8048
    • Lee, G.1    Han, C.H.2    Yoon, E.S.3
  • 20
    • 3042632377 scopus 로고    scopus 로고
    • Statistical monitoring of dynamic processes based on dynamic independent component analysis
    • Lee J.M., Yoo C.K., and Lee I.B. Statistical monitoring of dynamic processes based on dynamic independent component analysis. Chemical Engineering Science 59 (2004) 2995-3006
    • (2004) Chemical Engineering Science , vol.59 , pp. 2995-3006
    • Lee, J.M.1    Yoo, C.K.2    Lee, I.B.3
  • 21
    • 33645880467 scopus 로고    scopus 로고
    • Improved reliability in diagnosing faults using multivariate statistics
    • Lieftucht D., Kruger U., and Irwin G.W. Improved reliability in diagnosing faults using multivariate statistics. Computers and Chemical Engineering 30 5 (2006) 901-912
    • (2006) Computers and Chemical Engineering , vol.30 , Issue.5 , pp. 901-912
    • Lieftucht, D.1    Kruger, U.2    Irwin, G.W.3
  • 22
    • 0033096854 scopus 로고    scopus 로고
    • Face recognition using the nearest feature line method
    • Li S.Z., and Lu J.W. Face recognition using the nearest feature line method. IEEE Transactions on Neural Networks 10 (1999) 439-443
    • (1999) IEEE Transactions on Neural Networks , vol.10 , pp. 439-443
    • Li, S.Z.1    Lu, J.W.2
  • 25
    • 0041355444 scopus 로고    scopus 로고
    • Combination method of principal component and wavelet analysis for multivariate process monitoring and fault diagnosis
    • Lu N.Y., Wang F.L., and Gao F.R. Combination method of principal component and wavelet analysis for multivariate process monitoring and fault diagnosis. Industrial & Engineering Chemistry Research 42 (2003) 4198-4207
    • (2003) Industrial & Engineering Chemistry Research , vol.42 , pp. 4198-4207
    • Lu, N.Y.1    Wang, F.L.2    Gao, F.R.3
  • 26
    • 0033337021 scopus 로고    scopus 로고
    • Mika, S., Ratsch, G., & Weston, J. (1999). Fisher discriminant analysis with kernels. Neural Networks for Signal Processing Workshop (pp. 41-48). Madison, WI.
    • Mika, S., Ratsch, G., & Weston, J. (1999). Fisher discriminant analysis with kernels. Neural Networks for Signal Processing Workshop (pp. 41-48). Madison, WI.
  • 28
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • Schölkopf B., Smola A.J., and MJuller K. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation 10 5 (1998) 1299-1399
    • (1998) Neural Computation , vol.10 , Issue.5 , pp. 1299-1399
    • Schölkopf, B.1    Smola, A.J.2    MJuller, K.3
  • 29
    • 17844365596 scopus 로고    scopus 로고
    • Artificial neural network and support vector machine approach for locating faults in radial distribution systems
    • Thukaram D., Khincha H.P., and Vijaynarasimha H.P. Artificial neural network and support vector machine approach for locating faults in radial distribution systems. IEEE Transactions on Power Delivery 20 2 (2005) 710-721
    • (2005) IEEE Transactions on Power Delivery , vol.20 , Issue.2 , pp. 710-721
    • Thukaram, D.1    Khincha, H.P.2    Vijaynarasimha, H.P.3
  • 31
    • 0034858173 scopus 로고    scopus 로고
    • Wu, Y., Huang, T. S., & Toyama, K. (2001). Self-supervised learning for object based on kernel discriminant-EM algorithm. In Proceedings of International Conference on Computer Vision, (Vol. 1) (pp. 275-280). Kauai, HI.
    • Wu, Y., Huang, T. S., & Toyama, K. (2001). Self-supervised learning for object based on kernel discriminant-EM algorithm. In Proceedings of International Conference on Computer Vision, (Vol. 1) (pp. 275-280). Kauai, HI.
  • 32
    • 24144440092 scopus 로고    scopus 로고
    • Feature separation using ICA for a one-dimensional time series and its application in fault detection
    • Zuo M.J., Lin J., and Fan X.F. Feature separation using ICA for a one-dimensional time series and its application in fault detection. Journal of Sound and Vibration 287 (2005) 614-624
    • (2005) Journal of Sound and Vibration , vol.287 , pp. 614-624
    • Zuo, M.J.1    Lin, J.2    Fan, X.F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.