메뉴 건너뛰기




Volumn 40, Issue , 2016, Pages 24-34

On the use of reconstruction-based contribution for fault diagnosis

Author keywords

Chi square contribution; Fault diagnosis; Multivariate statistical process monitoring; Principal component analysis; Reconstruction based contribution

Indexed keywords

FAILURE ANALYSIS; MULTIVARIANT ANALYSIS; NUMERICAL METHODS; PRINCIPAL COMPONENT ANALYSIS; PROCESS CONTROL; PROCESS MONITORING; STATISTICAL PROCESS CONTROL;

EID: 84958183629     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2016.01.011     Document Type: Article
Times cited : (36)

References (33)
  • 2
    • 84875001041 scopus 로고    scopus 로고
    • Review of recent research on data-based process monitoring
    • Z.Q. Ge, Z.H. Song, and F.R. Gao Review of recent research on data-based process monitoring Ind. Eng. Chem. Res. 52 10 2013 3543 3562
    • (2013) Ind. Eng. Chem. Res. , vol.52 , Issue.10 , pp. 3543-3562
    • Ge, Z.Q.1    Song, Z.H.2    Gao, F.R.3
  • 3
    • 84897108321 scopus 로고    scopus 로고
    • Data-driven design of monitoring and diagnosis systems for dynamic processes: A review of subspace technique based schemes and some recent results
    • S.X. Ding Data-driven design of monitoring and diagnosis systems for dynamic processes: a review of subspace technique based schemes and some recent results J. Process Control 24 2 2014 431 449
    • (2014) J. Process Control , vol.24 , Issue.2 , pp. 431-449
    • Ding, S.X.1
  • 4
    • 83655192079 scopus 로고    scopus 로고
    • Guest editorial: Special section on data-based control, modeling, and optimization
    • T.Y. Chai, Z.S. Hou, F.L. Lewis, A. Hussain, and D.B. Zhao Guest editorial: Special section on data-based control, modeling, and optimization IEEE Trans. Neural Netw. 22 12 2011 2150 2153
    • (2011) IEEE Trans. Neural Netw. , vol.22 , Issue.12 , pp. 2150-2153
    • Chai, T.Y.1    Hou, Z.S.2    Lewis, F.L.3    Hussain, A.4    Zhao, D.B.5
  • 5
    • 0030530039 scopus 로고    scopus 로고
    • The process chemometrics approach to process monitoring and fault detection
    • B.M. Wise, and N.B. Gallagher The process chemometrics approach to process monitoring and fault detection J. Process Control 6 6 1996 329 348
    • (1996) J. Process Control , vol.6 , Issue.6 , pp. 329-348
    • Wise, B.M.1    Gallagher, N.B.2
  • 6
    • 0242354134 scopus 로고    scopus 로고
    • Statistical process monitoring: Basics and beyond
    • S.J. Qin Statistical process monitoring: basics and beyond J. Chemom. 17 8-9 2003 480 502
    • (2003) J. Chemom. , vol.17 , Issue.8-9 , pp. 480-502
    • Qin, S.J.1
  • 7
    • 0029252734 scopus 로고
    • Multivariate SPC charts for monitoring batch processes
    • P. Nomikos, and J.F. MacGregor Multivariate SPC charts for monitoring batch processes Technometrics 37 1 1995 41 59
    • (1995) Technometrics , vol.37 , Issue.1 , pp. 41-59
    • Nomikos, P.1    MacGregor, J.F.2
  • 8
    • 0030127409 scopus 로고    scopus 로고
    • Statistical process monitoring and disturbance diagnosis in multivariable continuous processes
    • A. Raich, and A. Cinar Statistical process monitoring and disturbance diagnosis in multivariable continuous processes AIChE J. 42 4 1996 995 1009
    • (1996) AIChE J. , vol.42 , Issue.4 , pp. 995-1009
    • Raich, A.1    Cinar, A.2
  • 9
    • 84866069902 scopus 로고    scopus 로고
    • A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process
    • S. Yin, S.X. Ding, A. Haghani, H.Y. Hao, and P. Zhang A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process J. Process Control 22 9 2012 1567 1581
    • (2012) J. Process Control , vol.22 , Issue.9 , pp. 1567-1581
    • Yin, S.1    Ding, S.X.2    Haghani, A.3    Hao, H.Y.4    Zhang, P.5
  • 10
    • 84869089680 scopus 로고    scopus 로고
    • Survey on data-driven industrial process monitoring and diagnosis
    • S.J. Qin Survey on data-driven industrial process monitoring and diagnosis Annu. Rev. Control 36 2 2012 220 234
    • (2012) Annu. Rev. Control , vol.36 , Issue.2 , pp. 220-234
    • Qin, S.J.1
  • 11
    • 33645402336 scopus 로고    scopus 로고
    • An improved PCA scheme for sensor FDI: Application to an air quality monitoring network
    • M.F. Harkat, G. Mourot, and J. Ragot An improved PCA scheme for sensor FDI: application to an air quality monitoring network J. Process Control 16 6 2006 625 634
    • (2006) J. Process Control , vol.16 , Issue.6 , pp. 625-634
    • Harkat, M.F.1    Mourot, G.2    Ragot, J.3
  • 12
    • 84857790824 scopus 로고    scopus 로고
    • Fault detection and isolation in transient states using principal component analysis
    • D. Garcia-Alvarez, M.J. Fuente, and G.I. Sainz Fault detection and isolation in transient states using principal component analysis J. Process Control 22 3 2012 551 563
    • (2012) J. Process Control , vol.22 , Issue.3 , pp. 551-563
    • Garcia-Alvarez, D.1    Fuente, M.J.2    Sainz, G.I.3
  • 13
    • 79952573528 scopus 로고    scopus 로고
    • Analysis and generalization of fault diagnosis methods for process monitoring
    • C.F. Alcala, and S.J. Qin Analysis and generalization of fault diagnosis methods for process monitoring J. Process Control 21 3 2011 322 330
    • (2011) J. Process Control , vol.21 , Issue.3 , pp. 322-330
    • Alcala, C.F.1    Qin, S.J.2
  • 14
    • 0034621628 scopus 로고    scopus 로고
    • Generalized contribution plots in multivariate statistical process monitoring
    • J.A. Westerhuis, S.P. Gurden, and A.K. Smilde Generalized contribution plots in multivariate statistical process monitoring Chemom. Intell. Lab. Syst. 51 1 2000 95 114
    • (2000) Chemom. Intell. Lab. Syst. , vol.51 , Issue.1 , pp. 95-114
    • Westerhuis, J.A.1    Gurden, S.P.2    Smilde, A.K.3
  • 15
    • 67349245154 scopus 로고    scopus 로고
    • Reconstruction-based contribution for process monitoring
    • C.F. Alcala, and S.J. Qin Reconstruction-based contribution for process monitoring Automatica 45 7 2009 1593 1600
    • (2009) Automatica , vol.45 , Issue.7 , pp. 1593-1600
    • Alcala, C.F.1    Qin, S.J.2
  • 16
    • 0031644999 scopus 로고    scopus 로고
    • A unified geometric approach to process and sensor fault identification and reconstruction: The unidimensional fault case
    • R. Dunia, and S.J. Qin A unified geometric approach to process and sensor fault identification and reconstruction: the unidimensional fault case Comput. Chem. Eng. 22 7-8 1998 927 943
    • (1998) Comput. Chem. Eng. , vol.22 , Issue.7-8 , pp. 927-943
    • Dunia, R.1    Qin, S.J.2
  • 17
    • 77956075435 scopus 로고    scopus 로고
    • Reconstruction-based contribution for process monitoring with kernel principal component analysis
    • C.F. Alcala, and S.J. Qin Reconstruction-based contribution for process monitoring with kernel principal component analysis Ind. Eng. Chem. Res. 49 17 2010 7849 7857
    • (2010) Ind. Eng. Chem. Res. , vol.49 , Issue.17 , pp. 7849-7857
    • Alcala, C.F.1    Qin, S.J.2
  • 18
    • 84905715757 scopus 로고    scopus 로고
    • Multi-directional reconstruction based contributions for root-cause diagnosis of dynamic processes
    • Portland, USA
    • G. Li, S.J. Qin, and T.Y. Chai Multi-directional reconstruction based contributions for root-cause diagnosis of dynamic processes American Control Conference (ACC) Portland, USA 2014 3500 3505
    • (2014) American Control Conference (ACC) , pp. 3500-3505
    • Li, G.1    Qin, S.J.2    Chai, T.Y.3
  • 19
    • 80051912783 scopus 로고    scopus 로고
    • Generalized reconstruction-based contributions for output-relevant fault diagnosis with application to the Tennessee Eastman process
    • G. Li, C.F. Alcala, S.J. Qin, and D.H. Zhou Generalized reconstruction-based contributions for output-relevant fault diagnosis with application to the Tennessee Eastman process IEEE Trans. Control Syst. Technol. 19 5 2011 1114 1127
    • (2011) IEEE Trans. Control Syst. Technol. , vol.19 , Issue.5 , pp. 1114-1127
    • Li, G.1    Alcala, C.F.2    Qin, S.J.3    Zhou, D.H.4
  • 20
    • 84862788679 scopus 로고    scopus 로고
    • Fault diagnosis of continuous annealing processes using a reconstruction-based method
    • Q. Liu, T.Y. Chai, and S.J. Qin Fault diagnosis of continuous annealing processes using a reconstruction-based method Control Eng. Pract. 20 5 2012 511 518
    • (2012) Control Eng. Pract. , vol.20 , Issue.5 , pp. 511-518
    • Liu, Q.1    Chai, T.Y.2    Qin, S.J.3
  • 21
    • 84880896724 scopus 로고    scopus 로고
    • Weighted reconstruction-based contribution for improved fault diagnosis
    • H.P. Xu, F. Yang, H. Ye, W.C. Li, P. Xu, and A.K. Usadi Weighted reconstruction-based contribution for improved fault diagnosis Ind. Eng. Chem. Res. 52 29 2013 9858 9870
    • (2013) Ind. Eng. Chem. Res. , vol.52 , Issue.29 , pp. 9858-9870
    • Xu, H.P.1    Yang, F.2    Ye, H.3    Li, W.C.4    Xu, P.5    Usadi, A.K.6
  • 22
    • 84900444831 scopus 로고    scopus 로고
    • Incipient sensor fault diagnosis based on average residual-difference reconstruction contribution plot
    • J.Y. Xuan, Z.G. Xu, and Y.X. Sun Incipient sensor fault diagnosis based on average residual-difference reconstruction contribution plot Ind. Eng. Chem. Res. 53 18 2014 7706 7713
    • (2014) Ind. Eng. Chem. Res. , vol.53 , Issue.18 , pp. 7706-7713
    • Xuan, J.Y.1    Xu, Z.G.2    Sun, Y.X.3
  • 23
    • 84934301267 scopus 로고    scopus 로고
    • Reconstruction-based contribution analysis approaches for improved fault diagnosis using principal component analysis
    • B. Mnassri, M. Eladel, and M. Ouladsine Reconstruction-based contribution analysis approaches for improved fault diagnosis using principal component analysis J. Process Control 33 2015 60 76
    • (2015) J. Process Control , vol.33 , pp. 60-76
    • Mnassri, B.1    Eladel, M.2    Ouladsine, M.3
  • 24
    • 0033230994 scopus 로고    scopus 로고
    • Selection of the number of principal components: The variance of the reconstruction error criterion with a comparison to other methods
    • S. Valle, W.H. Li, and S.J. Qin Selection of the number of principal components: the variance of the reconstruction error criterion with a comparison to other methods Ind. Eng. Chem. Res. 38 11 1999 4389 4401
    • (1999) Ind. Eng. Chem. Res. , vol.38 , Issue.11 , pp. 4389-4401
    • Valle, S.1    Li, W.H.2    Qin, S.J.3
  • 25
    • 0033903077 scopus 로고    scopus 로고
    • Determining the number of principal components for best reconstruction
    • S.J. Qin, and R. Dunia Determining the number of principal components for best reconstruction J. Process Control 10 2 2000 245 250
    • (2000) J. Process Control , vol.10 , Issue.2 , pp. 245-250
    • Qin, S.J.1    Dunia, R.2
  • 26
    • 0000235653 scopus 로고
    • Some theorems on quadratic forms applied in the study of analysis of variance problems, I. Effect of inequality of variance in the one-way classification
    • G.E.P. Box Some theorems on quadratic forms applied in the study of analysis of variance problems, I. effect of inequality of variance in the one-way classification Ann. Math. Stat. 25 2 1954 290 302
    • (1954) Ann. Math. Stat. , vol.25 , Issue.2 , pp. 290-302
    • Box, G.E.P.1
  • 27
    • 0030269512 scopus 로고    scopus 로고
    • Identification of faulty sensors using principal component analysis
    • R. Dunia, S.J. Qin, T.F. Edgar, and T.J. McAvoy Identification of faulty sensors using principal component analysis AIChE J. 42 10 1996 2797 2812
    • (1996) AIChE J. , vol.42 , Issue.10 , pp. 2797-2812
    • Dunia, R.1    Qin, S.J.2    Edgar, T.F.3    McAvoy, T.J.4
  • 28
    • 84864301166 scopus 로고    scopus 로고
    • Reconstruction-based multivariate contribution analysis for fault isolation: A branch and bound approach
    • B. He, X.H. Yang, T. Chen, and J. Zhang Reconstruction-based multivariate contribution analysis for fault isolation: a branch and bound approach J. Process Control 22 7 2012 1228 1236
    • (2012) J. Process Control , vol.22 , Issue.7 , pp. 1228-1236
    • He, B.1    Yang, X.H.2    Chen, T.3    Zhang, J.4
  • 29
    • 0035802262 scopus 로고    scopus 로고
    • Reconstruction-based fault identification using a combined index
    • H.H. Yue, and S.J. Qin Reconstruction-based fault identification using a combined index Ind. Eng. Chem. Res. 40 20 2001 4403 4414
    • (2001) Ind. Eng. Chem. Res. , vol.40 , Issue.20 , pp. 4403-4414
    • Yue, H.H.1    Qin, S.J.2
  • 30
    • 78149280345 scopus 로고    scopus 로고
    • A branch and bound method for isolation of faulty variables through missing variable analysis
    • V. Kariwala, P. Odiowei, Y. Cao, and T. Chen A branch and bound method for isolation of faulty variables through missing variable analysis J. Process Control 20 10 2010 1198 1206
    • (2010) J. Process Control , vol.20 , Issue.10 , pp. 1198-1206
    • Kariwala, V.1    Odiowei, P.2    Cao, Y.3    Chen, T.4
  • 31
    • 84884928551 scopus 로고    scopus 로고
    • Analysis of smearing-out in contribution plot based fault isolation for statistical process control
    • P.V. den Kerkhof, J. Vanlaer, G. Gins, and J.V. Impe Analysis of smearing-out in contribution plot based fault isolation for statistical process control Chem. Eng. Sci. 104 2013 285 293
    • (2013) Chem. Eng. Sci. , vol.104 , pp. 285-293
    • Den Kerkhof, P.V.1    Vanlaer, J.2    Gins, G.3    Impe, J.V.4
  • 32
    • 84861734299 scopus 로고    scopus 로고
    • Leakage fault diagnosis for an internet-based three-tank system: An experimental study
    • D.H. Zhou, X. He, Z.D. Wang, G.P. Liu, and Y.D. Ji Leakage fault diagnosis for an internet-based three-tank system: an experimental study IEEE Trans. Control Syst. Technol. 20 4 2012 857 870
    • (2012) IEEE Trans. Control Syst. Technol. , vol.20 , Issue.4 , pp. 857-870
    • Zhou, D.H.1    He, X.2    Wang, Z.D.3    Liu, G.P.4    Ji, Y.D.5
  • 33
    • 84886694214 scopus 로고    scopus 로고
    • A data-based state feedback control method for a class of nonlinear systems
    • Z. Wang, and D.R. Liu A data-based state feedback control method for a class of nonlinear systems IEEE Trans. Ind. Inform. 9 4 2013 2284 2292
    • (2013) IEEE Trans. Ind. Inform. , vol.9 , Issue.4 , pp. 2284-2292
    • Wang, Z.1    Liu, D.R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.