Railway Wheel Flat Detection Based on Improved Empirical Mode Decomposition

• Main Authors: Yifan Li, Jianxin Liu, Yan Wang
• Format: Article
• Language: English
• Published: Hindawi Limited 2016-01-01
• Series: Shock and Vibration
• Online Access: http://dx.doi.org/10.1155/2016/4879283

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.