摘要
爆破信号测试过程中,受测试环境和仪器自身原因的影响,在爆破近区监测到的信号往往含有趋势项干扰,无法实现信号特征的精细化提取。对现场爆破信号进行有效采集,采用变分模态分解(Variational mode decomposition,VMD)对其进行了趋势项消除并进行了时频特征提取。结果表明:井筒爆破振动信号中的趋势项具有高幅、低频特征,在时间轴上的分布更为广泛,信号中的真实成分具有宽频、低幅特征,在时间轴上聚集性更强,两者具有显著的区分度,变分模态分解对于爆破信号的自适应性强,可有效避免模态混叠效应的产生。
In the test process of blasting signal,influenced by the test environment and the instrument,the signals detected near blasting area often contain the trend item interference,which cannot achieve the fine extraction of signal characteristics.The blasting signals are effectively collected,and the trend items are eliminated and the time-frequency characteristics are extracted using the variational mode decomposition(VMD).The results show that:the trend term of blasting vibration signal has the characteristics of high amplitude and low frequency;it’s more broadly distributed in time.The real components in the signal have the characteristics of wide frequency and low amplitude,and the aggregation is stronger on the time axis,there is a significant degree of differentiation between them.The variational mode decomposition is highly adaptive to the blasting signal and can effectively avoid the generation of the mode aliasing effect.
作者
付晓强
崔秀琴
杨立云
雷振
蔡雪霁
李阳
FU Xiaoqiang;CUI Xiuqin;YANG Liyun;LEI Zhen;CAI Xueji;LI Yang(School of Civil Engineering,Sanming University,Sanming 365004,China;Key Laboratory of Engineering Material&Structure Reinforement in Fujian Province Colleges(Sanming University),Sanming 365004,China;School of Mechanics and Civil Engineering,China University of Mining and Technology(Beijing),Beijing 100083,China;Institute of Mining Engineering,Guizhou Institute of Technology,Guiyang 550003,China)
出处
《煤矿安全》
CAS
北大核心
2020年第10期248-252,共5页
Safety in Coal Mines
基金
福建省自然科学基金高校联合基金资助项目(2020J01390)
三明学院科学研究发展基金暨福建省中青年教师教育科研资助项目(JAT190697,B201910)
三明市引导性科技项目计划资助项目(2019-S-28)。
关键词
竖井爆破
爆破振动
变分模态分解
时频分析
特征提取
shaft blasting
blasting vibration
variational mode decomposition
time frequency analysis
feature extraction
