模式自适应连续小波去除趋势项方法在爆破振动信号分析中的应用

发布时间：2018-04-10 00:31

本文选题：爆破振动　切入点：能量分布　出处：《爆炸与冲击》2017年02期

【摘要】：为了更精确提取爆破振动信号峰值速度、能量等重要特征,必须对爆破振动加速度信号时域积分中的趋势项予以去除。通过对实测爆破振动加速度信号进行梯形数值积分,提出以时域积分后的爆破振动速度信号来构造模式自适应小波基的方法,并用此方法去除时域积分后爆破振动速度信号中的趋势项,然后对去除趋势项后的爆破振动速度信号进行能量特征分析。结果表明:模式自适应连续小波法成功去除了时域积分后爆破振动速度信号中的趋势项;与建立在传统Fourier变换基础上的频谱分析相比,小波变换的能量分析具有更精细的频率分辨率,更适合于对频率分辨率要求更高的爆破振动信号进行分析;各频率区间范围划分越宽,爆破振动加速度信号与速度信号各频率区间内能量分布的相关程度越高,反之,相关程度越低。
[Abstract]:In order to extract more accurately the peak velocity, energy and other important characteristics of blasting vibration signal, it is necessary to remove the trend term from the time domain integral of blasting vibration acceleration signal.Based on the trapezoidal numerical integration of the measured blasting vibration acceleration signal, a method of constructing the mode adaptive wavelet basis is proposed by using the blasting vibration velocity signal after the time domain integration.This method is used to remove the trend term in the blasting vibration velocity signal after the time domain integration, and then the energy characteristic analysis of the blasting vibration velocity signal after removing the trend term is carried out.The results show that the mode adaptive continuous wavelet method has successfully removed the trend term from the velocity signal of blasting vibration after time domain integration, and compared with the spectrum analysis based on the traditional Fourier transform.The energy analysis of wavelet transform has more precise frequency resolution, which is more suitable for the analysis of blasting vibration signals with higher frequency resolution.The higher the correlation degree of the energy distribution between the acceleration signal of blasting vibration and the velocity signal is, the lower the correlation degree is.
【作者单位】：长沙理工大学土木与建筑学院;湖南城市学院土木工程学院;
【基金】：国家自然科学基金项目(51678071,51608183,51508037) 湖南省自然科学基金项目(2016JJ4013) 湖南省教育厅重点科学研究项目(16A038);湖南省教育厅科学研究项目(14B007)
【分类号】：TB53;TN911.6

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