• DocumentCode
    3049260
  • Title

    Multisensor Correlation Analysis and its Application in Coal Mines

  • Author

    Li, Aiguo ; Song, Lina

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Xi´´an Univ. of Sci. & Technol., Xi´´an, China
  • Volume
    2
  • fYear
    2009
  • fDate
    19-21 May 2009
  • Firstpage
    408
  • Lastpage
    412
  • Abstract
    A multisensor system in coal mine is composed of a dozen even dozens of gas monitoring sensors. There is coupling in sensors of the gas monitoring systems. And it is interesting. The paper focuses on two topics about correlation analysis for multisensor system. One is about multisensor correlation analysis. Correlation information entropy and condition number of matrix were used. The other is about how to effective find out all combinations correlation sensors in a multisensor system. A theorem was proposed in this paper. Based on the theorem, an algorithm which can find out all combinations of correlative sensors from a multisensor system is proposed. Proposed algorithm can not only find out all combinations of correlation sensors effectively, but obtain the maximum combination of correlation sensors. Through experiment on a real gas monitoring dataset in coal mine, the results of experiments show that performances of proposed algorithm are excellent.
  • Keywords
    data analysis; mining; sensor fusion; coal mines; correlation information entropy; correlative sensors combinations; gas monitoring dataset; gas monitoring sensors; gas monitoring systems; multisensor correlation analysis; multisensor system; Computer science; Computerized monitoring; Condition monitoring; Explosions; Gas detectors; Information entropy; Matrix decomposition; Multisensor systems; Sensor phenomena and characterization; Sensor systems; coal mines; gas monitor; multisensor correlation analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3571-5
  • Type

    conf

  • DOI
    10.1109/GCIS.2009.79
  • Filename
    5209409