A study on method of signal denoising based on wavelet transform for micro-seismicity monitoring in large-scale rockmass structures

This paper applied wavelet denoising method to monitoring micro-seismicity in large-scale rockmass structure. The feasibility of using symlet6 inwavelet denoising was validated with MATLAB simulation. Then four types of adaptive threshold rules for wavelet denoising are used to denoise three noisy signals. The result shows that the noise in signals can be filtered effectively with the four threshold rules and the Rigrsure threshold for wavelet denoising is more effective with the least mean square deviation and highest signal to noise ratio. Based on the multi-channel digital microseism monitoring system in Shizhuyuan mine, this paper applied wavelet denoising method to three different microseismic signals with the result of MATLAB simulation. The results show that the true microseismic signals can be recovered from the noisy signals by removing noise at every wavelet scale, even though noisy signals have low signal to noise ratio or include wide frequency range. The wavelet threshold denoising is suited especially to the denoising of microseismic monitoring signals in large-scale rockmass structures.