Aiming at the limitations of traditional wavelet transformation in feature extraction and analysis of blasting vibration signals, a combination method of

Tunable Q-factor wavelet Transform(TQWT) and Complementary Ensemble Empirical Mode Decomposition(CEEMD) signal refine feature extraction was proposed. Presetting tunable wavelet TQWT high and low quality factors’ parameters, the reconstructed signals obtained with dominant components of CEEMD were decomposed. The relative weighted factor θ was introduced to optimize the decomposition process. The fine feature extraction of blasting vibration signals was realized. Analysis results showed that the combination method is not dependent on choices of priori wavelet basis to analyze blasting vibration signals, two filterings of signals are realized in the decomposition process; through comparing continuous wavelet multi-scale 3D spectrum and time frequency wavelet ridge lines, the optimal analysis signals obtained with the decomposition of the combined algorithm can truly reflect the details of vibration signals, the time-frequency resolution rate is higher; the combined method suppresses the interference of clutter wave components to signals’ characteristics, it can extract accurately the characteristics information of blasting vibration signals under complex environment.