摘要
岩样破裂声发射信号中包含破裂关键时频信息,探究信号参数与岩样破裂前兆特征之间的关系对岩石工程灾害的预测具有现实意义。传统的伪维格纳分布(Pseudo Wigner-Ville Distribution,PWVD)算法能够通过对信号加窗来突出信号的局部特征,但是试验采集的信号一般是实值,直接运用PWVD进行时频分析可能会出现虚假频谱的情况。针对该问题,提出了一种基于Hilbert变换(Hilbert Transform,HT)的HPWVD时频分析方法对声发射信号展开时频研究。首先通过单轴压缩试验采集到钨岩、砂岩的破裂声发射信号;然后运用参数分析法对2种岩样累计振铃计数及累计能量的分布特征展开分析,并由此划分破裂阶段及确定破裂阶段临界点;最后运用HPWVD算法获取临界点前后的声发射信号的时频特征。研究结果表明,运用HPWVD算法对信号进行时频分析能够很好地消除虚假频谱的现象,并能准确获取临界点前后的时频信息,即岩样在破裂前的能量会在新的频段内重新分布与聚集,为岩样破裂预测提供了依据。
Acoustic emission signals resulting from rock fracture contain time-frequency information.Exploring the relationship between signal parameters and precursory characteristics of rock fracture has practical significance for the prediction of rock engineering disasters.The traditional Pseudo Wigner-Ville Distribution(PWVD)algorithm can highlight the local characteristics of the signal by windowing the signal,but the signals collected in the test are generally real values.If PWVD is directly used for time-frequency analysis,there may be a false spectrum.To solve this problem,a time-frequency analysis method of PWVD based on the Hilbert transform(HPWVD)is proposed to study the time-frequency of acoustic emission signals.Firstly,the acoustic emission signals of the tungsten rock and sandstone are collected during uniaxial compression tests.Then the parameter analysis method is used to analyze the cumulative ringing count and the distribution characteristics of cumulative energy of the two kinds of rock samples,so as to divide the fracture stage and determine the critical point of the fracture stage.Finally,the HPWVD algorithm is used to obtain the time-frequency characteristics of acoustic emission signals before and after the critical point.The results show that using the HPWVD algorithm to analyze the signal with time-frequency can eliminate the phenomenon of the false frequency spectrum,and can accurately obtain the time-frequency information before and after the critical point,that is,the energy of the rock before fracture will be redistributed in the new frequency band,provideing a basis for rock fracture prediction.
作者
杨丽荣
黎嘉骏
江川
黄祥海
YANG Lirong;LI Jiajun;JIANG Chuan;HUANG Xianghai(School of Mechanical and Electrical Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China)
出处
《采矿与岩层控制工程学报》
北大核心
2023年第1期63-73,共11页
Journal of Mining and Strata Control Engineering
基金
江西省教育厅科技资助项目(GJJ190452)。
关键词
岩样破裂
声发射参数分析
时频特性
HPWVD
单轴压缩试验
rock sample fracture
acoustic emission parameter analysis
time frequency characteristics
HPWVD
uniaxial compression test