• DocumentCode
    2999660
  • Title

    Beam-pumping unit energy-saving control system based on support vector machine

  • Author

    Gao, Meijuan ; Tian, Jingwen ; Zhou, Shiru ; Zhang, Fan

  • fYear
    2008
  • fDate
    1-3 Sept. 2008
  • Firstpage
    1864
  • Lastpage
    1869
  • Abstract
    Considering the issues that the energy saving process for beam-pumping unit is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The support vector machine (SVM) has the ability of strong nonlinear function approach, it has the ability of strong generalization and it also has the feature of global optimization. In this paper, an intelligent energy-saving control system of beam-pumping unit based on regression SVM is presented. Moreover, we propose a self-adaptive parameter adjust iterative algorithm to confirm SVM parameters. The parameters of energy-saving control process of beam-pumping unit are measured using multi sensors, and then the control system can control the working state of beam-pumping unit real-time. The system is used in the oil recovery plant. The experimental results prove that this system is feasible and effective.
  • Keywords
    generalisation (artificial intelligence); iterative methods; nonlinear control systems; petroleum industry; production engineering computing; pumps; regression analysis; support vector machines; beam-pumping unit; complicated system; global optimization; intelligent energy-saving control system; multisensors; nonlinear function approach; nonlinear system; oil recovery plant; regression support vector machine; self-adaptive parameter adjust iterative algorithm; strong generalization; Control systems; Energy measurement; Intelligent control; Intelligent sensors; Intelligent systems; Iterative algorithms; Machine intelligence; Nonlinear systems; Process control; Support vector machines; Beam-pumping unit; Energy-saving control; Support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-2502-0
  • Electronic_ISBN
    978-1-4244-2503-7
  • Type

    conf

  • DOI
    10.1109/ICAL.2008.4636462
  • Filename
    4636462