• DocumentCode
    724231
  • Title

    A monitoring method based on combination of EPCA and RPCA

  • Author

    Wang Xiao-gang ; Sun Jie ; Hu Hao ; Sha Yi ; Zhu Chun-li

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2015
  • fDate
    23-25 May 2015
  • Firstpage
    2752
  • Lastpage
    2757
  • Abstract
    Process monitoring is a very important measure which ensures process safety and stable operation. Considering the insufficient process information at the very beginning of new process and the necessity that process model needs to be updated constantly in order to adapt to process changes, a method based on a combination of extended principal component analysis (EPCA) and recursive principal component analysis (RPCA) is proposed in this article. Afterwards, the method proposed is applied in grinding processes and simulated, which shows that the method can not only effectively solve the problem of critical shortage of process information when a new process is run, but also improve the utilization rate of the normal followed-up samples, making process model more adaptable to process variability. Finally, the simulations results illustrate effectiveness and practicality of the investigated method.
  • Keywords
    grinding; principal component analysis; process monitoring; EPCA; RPCA; extended principal component analysis; grinding processes; process monitoring; process safety; recursive principal component analysis; Adaptation models; Data models; Matrix decomposition; Monitoring; Principal component analysis; Process control; Simulation; EPCA; Grinding Process; Process Monitoring; RPCA;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2015 27th Chinese
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-7016-2
  • Type

    conf

  • DOI
    10.1109/CCDC.2015.7162397
  • Filename
    7162397