• DocumentCode
    1680589
  • Title

    Surge Diagnosis of Mine Main Ventilator Based on Information Fusion

  • Author

    Wang, Xin ; Jiang, Jun ; Hao, Yumeng

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Henan Polytech. Univ., Jiaozuo, China
  • fYear
    2012
  • Firstpage
    683
  • Lastpage
    686
  • Abstract
    The surge fault is the severe fault of the mine main ventilator. In order to improve the reliability of the surge diagnosis of the mine main ventilator, this paper presents a new surge diagnosis method based on the multi-sensor information fusion. A novel calculating method of the mass function based on the fuzzy set is put forward. According to the characteristics of the surge diagnosis of the mine main ventilator, the membership functions are obtained. By using the membership functions, the mass functions are obtained, and then by using the Dempster-Shafer evidential theory, the information fusion is carried out. This paper presents the implementing process of the surge diagnosis of the mine main ventilator in detail. The surge diagnosis results indicate that the multi-sensor information fusion can improve the accuracy and reliability of the surge diagnosis of the mine main ventilator effectively.
  • Keywords
    fault diagnosis; fuzzy set theory; inference mechanisms; mining; reliability; sensor fusion; ventilation; Dempster-Shafer evidential theory; fault diagnosis; fuzzy set; mass function; membership function; mine main ventilator; multisensor information fusion; reliability; severe fault; surge diagnosis; surge fault; Equations; Fault diagnosis; Sensor fusion; Surges; Vibrations; Dempster-Shafer(D-S) evidential theory; fault diagnosis; information fusion; mine main ventilator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
  • Conference_Location
    Hunan
  • Print_ISBN
    978-1-4673-0458-0
  • Type

    conf

  • DOI
    10.1109/CDCIEM.2012.167
  • Filename
    6178594