• Title of article

    Railway Wheel Flat Detection Based on Improved Empirical Mode Decomposition

  • Author/Authors

    Li, Yifan Department of Mechanical Engineering - Southwest Jiaotong University, China , Liu, Jianxin Traction Power State Key Laboratory - Southwest Jiaotong University, China , Wang, Yan Department of Mechanical Engineering - Southwest Jiaotong University, China

  • Pages
    15
  • From page
    1
  • To page
    15
  • Abstract
    This study explores the capacity of the improved empirical mode decomposition (EMD) in railway wheel flat detection. Aiming at the mode mixing problem of EMD, an EMD energy conservation theory and an intrinsic mode function (IMF) superposition theory are presented and derived, respectively. Based on the above two theories, an improved EMD method is further proposed. The advantage of the improved EMD is evaluated by a simulated vibration signal. Then this method is applied to study the axle box vibration response caused by wheel flats, considering the influence of both track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method is verified by a test rig experiment. Research results demonstrate that the improved EMD can inhibit mode mixing phenomenon and extract the wheel fault characteristic effectively.
  • Keywords
    Railway Wheel , Flat Detection , Improved Empirical , Mode Decomposition
  • Journal title
    Shock and Vibration
  • Serial Year
    2016
  • Record number

    2616163