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Volume 38 Issue 10
Oct.  2012
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Journal of Beijing University of Aeronautics and Astronautics  > 2012  >  38(10): 1295-1299.
Du Fuzhou, Tang Xiaoqing. Method of MSPC fault detection and diagnosis based on variable contributions[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(10): 1295-1299. (in Chinese)
Citation: Du Fuzhou, Tang Xiaoqing. Method of MSPC fault detection and diagnosis based on variable contributions[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(10): 1295-1299. (in Chinese)
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Method of MSPC fault detection and diagnosis based on variable contributions

  • School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • Received Date: 06 Nov 2011
  • Publish Date: 30 Oct 2012
    Abstract
  • Fault detection and diagnosis is one of the key technologies on the effective application of multivariate statistical process control(MSPC). In order to overcome the historical fault information using shortage, considering the influence of principal components variable contributions and the reconstructive errors, the synthetical variable contributions were calculated by normalizing and summing these two different variable contributions. A novel MSPC fault detection and diagnosis method was proposed based on the integrated variable contributions, and the relevant algorithm and program were presented and implemented. A case study was illustrated through the Tennessee Eastman challenge process simulation platform. The experimental results demonstrate that the proposed method is feasible and valid.

     

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    • References(10)
  • [1]
    Lieftucht D,Kruger U,Irwin G W.Improved reliability in diagnosing faults using multivariate statistics[J].Computers and Chemical Engineering,2006,30:901-912
    [2]
    Bozorgtabar B,Noorian F,Rad G A.Comparison of different PCA based face recognition algorithms using genetic programming //5th International Symposium on Telecommunications.Tehran:IEEE,2010:801-805
    [3]
    El-Midany T T,El-Baz M A,Abd-Elwahed M S.A proposed framework for control chart pattern recognitions in multivariate process using artificial neural networks[J].Expert Systems with Applications,2010,37(2):1035-1042
    [4]
    Alkaya A,Eker I.A new threshold algorithm based PCA method for fault detection in transient state processes //7th International Conference on Electrical and Electronics Engineering.Piscataway,NJ:IEEE,2011:144-147
    [5]
    Yu Jianbo.Fault detection using principal components-based Gaussian mixture model for semiconductor manufacturing processes[J].IEEE Transactions on Semiconductor Manufactureing,2011,24(3):432-444
    [6]
    Stefatos G,Hamza A B.Fault detection and isolation of faults in a multivariate process with Bayesian network[J].Journal of Process Control,2010,20(8):902-911
    [7]
    杨英华.多元统计过程监测和故障诊断方法及其应用研究 .沈阳:东北大学信息科学与工程学院,2002 Yang Yinghua.Multivariate statistics based process monitoring and fault diagnosis method and its application .Shenyang:College of Information Science and Engineering,Northeastern University,2002 (in Chinese)
    [8]
    Yang Qingsong.Model-based and data driven fault diagnosis methods with applications to process monitoring .Cleveland:Department of Electrical Engineering and Computer Sciences,Case Western Reserve University,2004
    [9]
    Downs J J,Vogel E F.A plant-wide industrial process control problem[J].Computers and Chemical Engineering,1993,17(3):245-255
    [10]
    Chiang L H,Russell E L,Braatz R D.Fault diagnosis in chemical processes using fisher discriminant analysis,discriminant partial least squares,and principal component analysis[J].Chemometrics and Intelligent Laboratory Systems,2000,50:243-252
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