Fissure prediction based on wavelet transform and complex signal analysis technology

The fissure is one of the most important and active master control factors inducing geohazards such as water outburst and mud gushing. The precise and immediate forecasting fissure is a key problem to be studied and resolved currently in tunnel design and construction. Complex signal analysis is introduced to the prediction of water with the ground penetrating radar (GPR) to analyze the water response in the radar data from instantaneous amplitude, instantaneous phase and instantaneous frequency, therefore the accuracy of fissure prediction is improved. However, a large number of effective information in the instantaneous frequency will be covered by noise, thus affecting the accuracy of the prediction. To solve the problem, this paper proposes a method to improve the accuracy of fissure prediction by combining wavelet transform and complex signal analysis. In this method, wavelet transform can effectively suppress the noise, when there is no large loss of signal instantaneous frequency. At last, the engineering example demonstrates the validity of the proposed approach.