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

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。

Application of removal trend method of pattern adapted continuous wavelet to blast vibration signal analysis

To accurately characterize such important characteristics as the peak velocity and the energy distribution in different frequency ranges of the blast vibration signal,this signal's trend after the time integral has to be removed.In this paper,the trapezoidal numerical integration of the measured blast vibration acceleration signal was carried out,the blast vibration velocity signal after the time integral as a method for the wavelet basis was proposed,the trend of the blast vibration velocity signal after the time integral was removed using this method,and the characteristics of energy distribution in different frequency ranges of the signal after the trend removal was analyzed.The results show that the trend of the blast vibration velocity signal after the time integral was successfully removed using the pattern adapted wavelet method.Compared with the frequency spectra analysis based on the conventional Fourier transform,the energy analysis based on the wavelet transform had a higher frequency resolution and was more suitable for the analysis that satisfied a higher requirement of frequency resolution for the signal.The more widely divided the different frequency ranges,the higher the degree of the energy distribution correlation in different frequency ranges between the measured blast acceleration signal and the blast vibration velocity signal and,on the other hand,the less widely divided,the lower the degree of the correlation.