Trend Term and Noise Removal Method for Tunnel Blasting Vibration Signals Based on Fourier Decomposition

In order to reduce the impact of trend and noise components on the accuracy of tunnel blasting vibration signal processing, a preprocessing method for blasting vibration signals based on Fourier Decomposition Method (FDM) is proposed. Firstly, the measured blasting vibration signal is decomposed into a series of components through FDM, and the signal dominant component is obtained based on the principle of threshold selection. Then, the dominant components are reconstructed to obtain a pure signal after removing trend terms and noise, and the effectiveness of the method is verified using spectral analysis. The research results show that FDM can effectively separate low-frequency trend terms and high-frequency noise in blasting vibration signals. Compared with existing traditional methods, the pure signal time history curve obtained after FDM processing is the smoothest, with the highest signal-to-noise ratio (23.240 6) and the smallest root mean square difference (0.024 6), demonstrating good preprocessing performance.