Real-time monitoring of axle fracture of railway vehicles by translation invariant wavelet

The translation invariant wavelet can suppress Pseudo-Gibbs phenomenon, which is produced on the singularity points of signal by threshold method wavelet, and diminish RMSE between the original signal and estimated one. At the same time, SNR of estimated signal can also be improved. A burst of acoustic emission energy was used to inspect the fatigue cracks of axle of railway vehicle. The algorithm was implemented in a DSP board. The results demonstrate that this method can effectively eliminate noise, extract characteristic information of acoustic emission signals, and the proposed system shows an excellent monitoring capability.