메뉴 건너뛰기




Volumn 35, Issue 12, 2014, Pages 2673-2680

Nonlinear process fault detection method under noise environment using KPCA and MVU

Author keywords

Fault detection; KPCA; MVU; Nonlinear noisy data

Indexed keywords

DATA MINING; EXTRACTION; FEATURE EXTRACTION; MATHEMATICAL TRANSFORMATIONS; METADATA; PROCESS MONITORING;

EID: 84921651978     PISSN: 02543087     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (7)

References (15)
  • 1
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • TENENBAUM J B, SILVA V D, LANGFORD J C. A global geometric framework for nonlinear dimensionality reduction [J]. Science, 2000, 290: 2319-2323.
    • (2000) Science , vol.290 , pp. 2319-2323
    • Tenenbaum, J.B.1    Silva, V.D.2    Langford, J.C.3
  • 2
    • 2342517502 scopus 로고    scopus 로고
    • Think globally, fit locally: Unsupervised learning of low dimensional manifold
    • SAUL L K, ROWEIS S T. Think globally, fit locally: Unsupervised learning of low dimensional manifold [J]. Journal of Machine Learning Research, 2003, 4(4): 119-155.
    • (2003) Journal of Machine Learning Research , vol.4 , Issue.4 , pp. 119-155
    • Saul, L.K.1    Roweis, S.T.2
  • 3
    • 67650559655 scopus 로고    scopus 로고
    • LPMVP Algorithm and Its Application to Fault Detection
    • ZHANG M G, SONG ZH H. LPMVP Algorithm and Its Application to Fault Detection [J]. Acta automatica sinica, 2009, 35(6): 766-772.
    • (2009) Acta Automatica Sinica , vol.35 , Issue.6 , pp. 766-772
    • Zhang, M.G.1    Song, Z.H.2
  • 4
    • 84921648449 scopus 로고    scopus 로고
    • Improved MVU based fault detection method for nonlinear and dynamic process
    • CHEN R Q. Improved MVU based fault detection method for nonlinear and dynamic process [J]. Chinese Journal of Scientific Instrument, 2009, 30(3): 471-476.
    • (2009) Chinese Journal of Scientific Instrument , vol.30 , Issue.3 , pp. 471-476
    • Chen, R.Q.1
  • 5
    • 84885064046 scopus 로고    scopus 로고
    • Statistical process monitoring based on a multi-manifold projection algorithm
    • TONG CH D, YAN X F. Statistical process monitoring based on a multi-manifold projection algorithm [J]. Chemometrics and Intelligent Laboratory Systems, 2014, 130: 20-28.
    • (2014) Chemometrics and Intelligent Laboratory Systems , vol.130 , pp. 20-28
    • Tong, C.D.1    Yan, X.F.2
  • 6
    • 84903273173 scopus 로고    scopus 로고
    • Nonlinear process monitoring and fault isolation using extended maximum variance unfolding
    • LIU Y J, CHEN T, YAO Y. Nonlinear process monitoring and fault isolation using extended maximum variance unfolding [J]. Journal of Process Control, 2014, 24(6): 880-891.
    • (2014) Journal of Process Control , vol.24 , Issue.6 , pp. 880-891
    • Liu, Y.J.1    Chen, T.2    Yao, Y.3
  • 8
    • 58749115727 scopus 로고    scopus 로고
    • Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM
    • ZHANG Y W. Enhanced statistical analysis of nonlinear processes using KPCA, KICA and SVM [J]. Chemical Engineering Science, 2009, 64: 801-811.
    • (2009) Chemical Engineering Science , vol.64 , pp. 801-811
    • Zhang, Y.W.1
  • 9
    • 77952130972 scopus 로고    scopus 로고
    • KPCA and LSSVM model-based slag basicity prediction for silicomanganese smelting process
    • TANG CH X, YANG CH H, GUI W H. KPCA and LSSVM model-based slag basicity prediction for silicomanganese smelting process [J]. Chinese Journal of Scientific Instrument, 2010, 31 (3): 689-693.
    • (2010) Chinese Journal of Scientific Instrument , vol.31 , Issue.3 , pp. 689-693
    • Tang, C.X.1    Yang, C.H.2    Gui, W.H.3
  • 10
    • 84880623050 scopus 로고    scopus 로고
    • Weighted kernel principal component analysis based on probability density estimation and moving window and its application in nonlinear chemical process monitoring
    • JIANG Q C, YAN X F. Weighted kernel principal component analysis based on probability density estimation and moving window and its application in nonlinear chemical process monitoring [J]. Chemometrics and Intelligent Laboratory Systems, 2013, 127(15): 121-131.
    • (2013) Chemometrics and Intelligent Laboratory Systems , vol.127 , Issue.15 , pp. 121-131
    • Jiang, Q.C.1    Yan, X.F.2
  • 12
    • 84903465428 scopus 로고    scopus 로고
    • Shrinkage estimator in normal mean vector estimation based on conditional maximum likelihood estimators
    • PARK J. Shrinkage estimator in normal mean vector estimation based on conditional maximum likelihood esti-mators [J]. Statistics & Probability Letters, 2014, 93: 1-6.
    • (2014) Statistics & Probability Letters , vol.93 , pp. 1-6
    • Park, J.1
  • 13
    • 0037411806 scopus 로고    scopus 로고
    • Exploring process data with the use of robust outlier detection algorithms
    • LEO H C, RANDY J P, MARY B S. Exploring process data with the use of robust outlier detection algorithms [J]. Journal of Process Control, 2003, 13(5): 437-449.
    • (2003) Journal of Process Control , vol.13 , Issue.5 , pp. 437-449
    • Leo, H.C.1    Randy, J.P.2    Mary, B.S.3
  • 14
    • 65349170020 scopus 로고    scopus 로고
    • New monitoring method for dynamic non-Gaussian process
    • WANG P L, YAN W J. New monitoring method for dynamic non-Gaussian process [J]. Chinese Journal of Scientific Instrument, 2009, 30(3): 471-476.
    • (2009) Chinese Journal of Scientific Instrument , vol.30 , Issue.3 , pp. 471-476
    • Wang, P.L.1    Yan, W.J.2
  • 15
    • 71849088402 scopus 로고    scopus 로고
    • Sensor fault identification and isolation for multivariate non-Gaussian processes
    • GE Z Q, XIE L, UWE K. Sensor fault identification and isolation for multivariate non-Gaussian processes [J]. Journal of Process Control, 2009, 19: 1707-1715.
    • (2009) Journal of Process Control , vol.19 , pp. 1707-1715
    • Ge, Z.Q.1    Xie, L.2    Uwe, K.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.