• DocumentCode
    3036673
  • Title

    Grey Prediction of Elbow Corrosion on Refinery Equipment

  • Author

    Wang, Zhengfang ; Wang, Yong ; Wang, Weiqiang ; Lu, Chuanyi ; Li, Chaowen

  • Author_Institution
    Inst. of Mech. Eng., China Univ. of Pet., Dongying
  • fYear
    2009
  • fDate
    8-10 March 2009
  • Firstpage
    75
  • Lastpage
    78
  • Abstract
    Shengli refinery plant process Middle-east crude oil, the equipment is exposed to wash erosion seriously. The elbow on the entrance of the atmospheric distillation tower top exchangers always leak for eroding. Measured the thickness of elbow by ultrasonic thickness meter every month, find the accumulating generation operator of remnant thickness is quasi smooth sequence, established GM (1, 1 ) model with grey system theory, detected the error with relative error, model passed error check, is eligible. Used full data to create improved GM (1, 1) model to predict elbowdasias thickness in the future. The elbow life can reach to 24 month, but can not reach to 36 month. Select place to measure thickness by experience is out of truth. Use Fluent to emulate fluid field can help to find the place to monitor.
  • Keywords
    crude oil; distillation equipment; erosion; grey systems; industrial plants; oil refining; thickness measurement; Fluent; GM (1, 1) model; Middle-east crude oil; Shengli refinery plant; atmospheric distillation tower top exchangers; elbow corrosion; grey prediction; grey system theory; model passed error check; refinery equipment; ultrasonic thickness meter; Atmospheric modeling; Corrosion; Elbow; Mechanical engineering; Petroleum; Poles and towers; Predictive models; Refining; Thickness measurement; Ultrasonic variables measurement; 1) model; GM (1; corrosion prediction; grey system model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Automation Engineering, 2009. ICCAE '09. International Conference on
  • Conference_Location
    Bangkok
  • Print_ISBN
    978-0-7695-3569-2
  • Type

    conf

  • DOI
    10.1109/ICCAE.2009.38
  • Filename
    4804492