隧道爆破信号主分量特征提取与毫秒延期识别研究

Principal Component Feature Extraction and Millisecond Delay Recognition of Tunnel Blasting Signal

为了准确揭示隧道爆破振动信号所包含的反映爆破特征参数的重要信息,通过EMD分解与交叉小波变换组合分析方法对实测爆破信号进行分析,得到各分量与原信号的相关性系数,从而准确判别出信号的主分量。再依据相关性系数对包含主分量在内的相关分量重组并进行Hilbert变换取模值,精确识别出隧道采用的各段别雷管的毫秒延期时间。结果表明:组合方法确定的主分量及相关分量重组信号能够突出爆破信号的主要特征,对隧道爆破信号的分析效果好。

In order to reveal the important information of blasting characteristic parameters contained in tunnel blasting vibration signals accurately,the measured blasting signal is analyzed by EMD decomposition and cross-wavelet transform,and the correlation coefficients between each component and the original signal are obtained,so as to accurately identify the principal component of the signal.And then,the correlation components including the principal component is reconstructed and the Hilbert transform is used to obtain the modulus value according to the correlation coefficient,and the millisecond delay time of each detonator used in the tunnel is accurately identified.The results show that the reconstructed signals of principal component and related ones determined by the combination method can highlight the main characteristics of blasting signals,and the analysis effect of the tunnel blasting signal is good.