Abstract
According to the fracture mechanics, Rail damage acoustic emission (AE) signal is related to the rail material, structure, load and crack development. For the rail with fixed material, fixed structure and load fluctuating in a small range, the rail damage can be monitored on-line by monitoring the AE signal. The existing AE signal processing technology can't simultaneously achieve noise suppression and high resolution transform domain representation. By introducing Wiger-Ville higher-order spectrum, the high resolution time-frequency domain two-dimensional representation of Rail damage AE signal under strong background Gauss noise is obtained successfully. The feature extraction and clustering analysis of Rail damage AE signal are realized. Accurate identification of rail damage AE signal of rail fracture, spalling of rail bottom, spalling of rail head, wheel/rail impact, friction of wheel flange, switching of pneumatic turnout, temperature force release is achieved. Theoretical analysis, experimental data (more than 3000), field data (more than 3 million) have proved the effectiveness and reliability of the method.
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