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Volumn 4, Issue 2, 2007, Pages 149-155

Sensor fault detection, isolation and reconstruction using nonlinear principal component analysis

Author keywords

Fault detection and isolation; Neural networks; Nonlinear PCA (NLPCA); Reconstruction

Indexed keywords

COMPUTER SIMULATION; MEASUREMENT THEORY; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; SENSORS;

EID: 34547313739     PISSN: 14768186     EISSN: 17518520     Source Type: Journal    
DOI: 10.1007/s11633-007-0149-6     Document Type: Article
Times cited : (46)

References (12)
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  • 3
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    • Identification of Faulty Sensors Using Principal Component Analysis
    • R. Dunia, S. J. Qin, T. F. Edgar, T. J. McAvoy. Identification of Faulty Sensors Using Principal Component Analysis. AIChE Journal, vol. 42, no. 10, pp. 2797-2812, 1996.
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    • Dunia, R.1    Qin, S.J.2    Edgar, T.F.3    McAvoy, T.J.4
  • 5
    • 0026113980 scopus 로고
    • Nonlinear Principal Component Analysis Using Auto-associative Neural Networks
    • M. A. Kramer. Nonlinear Principal Component Analysis Using Auto-associative Neural Networks. AIChE Journal, vol. 37, no. 2, pp. 233-243, 1991.
    • (1991) AIChE Journal , vol.37 , Issue.2 , pp. 233-243
    • Kramer, M.A.1
  • 6
    • 0043015539 scopus 로고    scopus 로고
    • Nonlinear Principal Component Analysis -Based on Principal Curves and Neural Networks
    • D. Dong, T. J. McAvoy. Nonlinear Principal Component Analysis -Based on Principal Curves and Neural Networks. Computers and Chemical Engineering, vol. 20, no. 1, pp. 65-78, 1996.
    • (1996) Computers and Chemical Engineering , vol.20 , Issue.1 , pp. 65-78
    • Dong, D.1    McAvoy, T.J.2
  • 7
    • 0029322882 scopus 로고
    • Reduction Data Dimensionality through Optimizing Neural Network Inputs
    • S. Tan, M. L. Mavrovouniotis. Reduction Data Dimensionality through Optimizing Neural Network Inputs. AIChE Journal, vol. 41, no. 6, pp. 1471-1480, 1995.
    • (1995) AIChE Journal , vol.41 , Issue.6 , pp. 1471-1480
    • Tan, S.1    Mavrovouniotis, M.L.2
  • 11
    • 33645395145 scopus 로고    scopus 로고
    • Sensor Fault Detection and Isolation of an Air Quality Monitoring Network Using Nonlinear Principal Component Analysis
    • Prague, Czech Republic
    • M. -F. Harkat, G. Mourot, J. Ragot. Sensor Fault Detection and Isolation of an Air Quality Monitoring Network Using Nonlinear Principal Component Analysis. In Proceedings of 16th IFAC Word Congress, Prague, Czech Republic, 2005.
    • (2005) Proceedings of 16th IFAC Word Congress
    • Harkat, M.-F.1    Mourot, G.2    Ragot, J.3
  • 12
    • 0034778304 scopus 로고    scopus 로고
    • Nonlinear Principal Component Analysis by Neural Networks
    • W. W. Hsieh. Nonlinear Principal Component Analysis by Neural Networks. Tellus, vol. 53A, no. 5, pp. 599-615, 2001.
    • (2001) Tellus , vol.53 A , Issue.5 , pp. 599-615
    • Hsieh, W.W.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.