• DocumentCode
    2811669
  • Title

    Research on fault diagnosis of HT-60 drilling rig based on neural network expert system

  • Author

    Liu, Yin ; Zhang, Weiming ; Liao, Zhixin

  • Author_Institution
    Fac. of Mech. & Electron. Inf., China Univ. of Geosci., Wuhan, China
  • Volume
    5
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    Combining the characteristics of drilling rig fault, a solution of fault diagnosis expert system based on artificial neural network is proposeed. The fault diagnosis system is designed for HT-60 drilling rig, which acquires knowledge by neural network and diagnoses by expert system. The system with characteristics of self-learning and self-adaptive can acquire knowledge from existing data in order to achieve the purpose of expanding knowledge, which maks up the inadequacies of traditional expert system. Through analyzing a variety of common faults and solutions, the software interface is established by using the Force Control software to achieve fault diagnosis which is based on artificial neural network expert system.
  • Keywords
    control engineering computing; diagnostic expert systems; drilling (geotechnical); electrical engineering computing; fault diagnosis; mechanical engineering computing; neural nets; HT-60 drilling rig fault diagnosis; artificial neural network expert system; force control software interface; Area measurement; Drilling; Torque; HT-60 drilling rig; expert system; fault diagnosis; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5619156
  • Filename
    5619156