Abstract:Wheel flats will influence ride comfort and result in rapid deterioration of vehicle and infrastructure components. A dynamic detection and identification method of wheel flat is proposed based on the rail vibration responses. A vehicle-track vertical coupling system and wheel flat are modelled and the rail dynamic responses are calculated with the condition of wheel flat. Two methods, Hilbert-Huang transformation (HHT) and higher-order spectrum, are compared which are used to analyze the rail vibration responses and identify the wheel flat. The influence of different track irregularity, train speed and wheel flat depth on the methods are analyzed. The Hilbert spectrum can qualitatively distinguish the normal wheel and the wheel with flats, but the detection ability is affected by the track irregularity. The high-order spectrum can express the different wheel flat depth quantitatively and it isn’t influenced by the track irregularity and train running speed. The investigation showed the rail vibration responses combined with high-order analysis can detect wheel flats effectively.
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