The Wheel Flat Identification Based on Variational Modal Decomposition—Envelope Spectrum Method of the Axlebox Acceleration

Abstract

The wheel flat can cause train and rail system infrastructure damage and endanger the running safety. To monitor the early wheel flat, it is urgent to carry out the theoretical basic research on the relationship between the vibration signal and the wheel flat. Moreover, to extract the characteristics of the wheel flat, an advanced and effective signal processing method need to be studied. A three-dimensional vehicle-track coupled dynamics model verified by field test is established based on the multi-body dynamics at first. The acceleration of the axlebox excited by the different wheel flat length is obtained by the dynamic simulation. The simulation considers the influence of various speeds and the short-wavelength track irregularities. Then, a combined method based on the variational modal decomposition (VMD) and the envelope spectrum (ES) is employed to detect the wheel flat signal. The feasibility of the method is further validated by comparing the co-existence of the wheel flat and the wheel eccentricity. Finally, field test is carried out to detect the wheel flat by using this method. The results indicate that the VMD-ES method accurately extracts the impact characteristics of the wheel flat and can quantitatively identify the wheel flat faults of small sizes.