基于TQWT能量选择算法隧道爆破信号特征提取分析  

Extraction and analysis of tunnel blasting signal characteristics based on TQWT energy selection algorithms

作　　者：付晓强 刘纪峰[1,2] 崔秀琴 张会芝[1,2] 张世平 雷振[4] FU Xiaoqiang;LIU Jifeng;CUI Xiuqin;ZHANG Huizhi;ZHANG Shiping;LEI Zhen(School of Civil Engineering,Sanming University,Sanming 365004,China;Key Laboratory of Engineering Material&Structure Reinforement in Fujian Province College(Sanming University),Sanming 365004,China;College of Mining Technology,Taiyuan University of Technology,Taiyuan 030024,China;Guizhou Institute of Technology,Institute of Mining Engineering,Guizhou,Guiyang 550003,China)

机构地区：[1]三明学院建筑工程学院,福建三明365004 [2]工程材料与结构加固福建省高等学校重点实验室,福建三明365004 [3]太原理工大学矿业工程学院,山西太原030024 [4]贵州理工学院,贵州贵阳550003

出　　处：《铁道科学与工程学报》2020年第2期405-412,共8页Journal of Railway Science and Engineering

基　　金：三明市引导性科技资助项目(2019-S-28);福建省中青年教师教育科研资助项目(JAT190697);三明学院引进高层次人才科研启动经费资助项目(18YG13)

摘　　要：以悬泉寺隧道掘进工程为背景,对隧道爆破振动进行监测。利用可调品质因子小波变换(Tunable Q-factor Wavelet Transform)优良的能量优化选择能力,实现信号高、低品质因子成分及所含高频强噪声的分离。通过对高、低品质因子优化分解子带能量人工判别,选取优势能量子带进行信号重组,得到最能体现信号特征的最佳分析信号。对最佳信号的分析结果表明:隧道爆破不同批次雷管混用导致MS3~MS5段间延时时差超过了设计值,爆破信号归一化短时傅里叶(Normalized Short Time Fourier Transform,NSTFT)时频分布说明隧道爆破主频与各段别起爆波形中心频率均值较为接近,体现了各段雷管起爆能量对信号能量分布的贡献。隧道爆破信号精细化分析在隧道爆破振动特征提取、雷管微差间隔识别和信号主频的判别等方面具有很好的工程应用价值。Based on the excavation project of Xuan-quansi Tunnel, the blasting vibration of the tunnel was effectively monitored. The tunable Q-factor Wavelet Transform was used to realize the separation of high and low quality factor components from high frequency and strong noise. Through the artificial discrimination of sub-band energy of optimal decomposition of high-and low-quality factors, the dominant energy sub-band was selected for signal reconstruction, and the most optimal analysis signal that best reflected the signal characteristics was obtained. The analysis results show that the delay time between MS3 and MS5 segments of the batch detonators used in tunnel blasting exceeds the design value due to the mixed use of different batches of detonators. The time-frequency distribution of the blasting signal in Normalized Short Time Fourier Transform(NSTFT) indicates that the main frequency of the tunnel blasting signal is close to that of the mean center frequency of the detonator wave in each section, which reflects the contribution of the detonator initiation energy to the energy distribution of the signal. The fine analysis of tunnel blasting signal has good engineering application value in the extraction of blasting vibration characteristics, the identification of detonator millisecond interval and the discrimination of main frequency of blasting signal.

关 键 词：铁路隧道 爆破振动 可调品质因子小波变换 能量特征 时频分析 

分 类 号：TD235.1[矿业工程—矿井建设]