基于FSWT时频分析的矿山微震信号分析与识别

采用频率切片小波变换技术(frequency slice wavelet transform,FSWT)对典型的矿山岩体微震信号和爆破振动信号进行了研究。首先利用FSWT分解一组信号,对两类波形进行了时频特性分析;然后利用其逆变换能切割任意频率区间的特点,构造6个连续的子频带并得到重构信号,并通过划分更细化的子频带,进行了两类信号不同的能量分布特性对比研究。研究结果表明:该矿山岩体微震信号和爆破振动信号的能量主要都分布于100 Hz以下,其中岩体微震信号的能量主要集中在0~50 Hz,爆破振动信号则主要集中在50~100 Hz;对于高于100 Hz区域,爆破振动信号所占能量比例更大。

Recognition of mine microseismic signals based on FSWT time-frequency analysis

Typical microseismic and blast vibration signals of mine rock mass are studied by using the frequency slice wavelet transform (FSWT). First, FSWT is used to decompose the signals in time and frequency domains, and time-frequency characteristics of two kinds of waveforms are analyzed. Next, owing to that the frequency bands can be chosen arbitrarily through inverse transform of FSWT, different energy distribution characteristics of the two kinds of signals are studied by building 6 continuous sub-bands so as to get the reconstructed signals, then the sub-bands are divided more narrowly for deeper researches. The results show that the energy of the two kinds of signals is mainly distributed below 100 Hz in this mine, and the difference is as follows: the energy of rock mass microseimic signals is mainly concentrated in the band between 0~50 Hz, but for the blast vibration signals, the energy is concentrated more obviously in the band between 50~100 Hz and has a higher energy proportion than that of the rock mass microseimic signals over 100 Hz.