Wavelet identification for the abnormal seismic wave component of rock burst

As we know, roof is composed of heterogeneous rock. When roof fractures, a large amount of energy would be released in the form of seismic wave. How to identify the abnormal signal of seismic wave is a much difficult problem, there are many methods used usually, such as Fourier Transformation, filter technique etc., but abnormal signal can't be recognized accurately. In this paper, multi-resolution wavelet technique is used to identify the first and second variation point, based on the Lipschitz $\alpha$. A living example analysis shows, multi-resolution wavelet technique can identify the abnormal signal of seismic wave effectively in different scale, and the omen of roof fall can be grasped in order to forecast the roof fall accurately. It provides a new idea for the predication of catastrophe on rock mechanics and engineering.