• DocumentCode
    2846281
  • Title

    Safety Prediction of Coalface Stray Current Based on BP ANN

  • Author

    Ma-Caoyuan ; Li-Guoxin ; Liang-rui ; Zhang-dongliang ; Dong-xinwei ; Tang-Jiejie

  • Author_Institution
    Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In order to realize safety prediction of workface stray current, it´s important to confirm the characteristic indexes of workface stray current so as to insure the time margin and reliability of prediction. By analyzing the resistance distribution network of the system, the paper confirms the four parameters as follows to be the characteristic indexes of coalface stray current safety prediction: the leakage current of contacting line, resistance of insulating splint, the distance between workface and subtraction substation and the stray voltage of contacting line. After that, the thesis built safety prediction model of coalface stray current danger grade with ANN as its core, chose the field measured data to do the training and prediction of safety prediction model and complete the designing and development of monitoring and predicting system of stray current. The results indicate that the proposed safety prediction model and the prediction system has strong applicability, it shows good effect.
  • Keywords
    backpropagation; coal; mining industry; neural nets; reliability theory; safety systems; artificial neural network; characteristic index; coalface stray current; contacting line leakage current; insulating splint resistance; prediction reliability; resistance distribution network; workface stray current safety prediction; workface-substation distance; Contact resistance; Current measurement; Electrical resistance measurement; Insulation; Leakage current; Monitoring; Predictive models; Railway safety; Substations; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5365093
  • Filename
    5365093