Research on energy distributions and fractal characteristics of Kaiser signal of acoustic emission in rock

ZHAO Kui; WAHG Geng-feng; WANG Xiao-jun; JIN Jie-fang; DENG Fei

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Research on energy distributions and fractal characteristics of Kaiser signal of acoustic emission in rock

更新时间：2026-06-25

- Research on energy distributions and fractal characteristics of Kaiser signal of acoustic emission in rock
- Vol. 29, Issue 11, (2008)
- 作者机构：
  
  1. 江西理工大学环境与建筑工程学院,江西,赣州,341000
  2. 北京科技大学土木与环境工程学院,北京,100083
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU454
- Online First：07 August 2013，
  
  Published：2008
- 稿件说明：
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ZHAO Kui, WAHG Geng-feng, WANG Xiao-jun, et al. Research on energy distributions and fractal characteristics of Kaiser signal of acoustic emission in rock[J]. 2008, 29(11).
DOI：

ZHAO Kui, WAHG Geng-feng, WANG Xiao-jun, et al. Research on energy distributions and fractal characteristics of Kaiser signal of acoustic emission in rock[J]. 2008, 29(11). DOI：

摘要

通过单轴加载岩石破坏全过程声发射试验，根据Kaiser效应原理采用参数法确定了Kaiser点。在此基础上，首先采用小波包频带分解方法，对岩石声发射Kaiser点信号的能量分布特征进行了研究，分析了砂岩声发射信号的不同频带能量分布规律，得到了Kaiser点特征频带能量百分比大于相邻点的重要结论。其次，采用G-P算法计算了声发射过程关联分维数，结果表明声发射过程不仅具有分形特征，而且Kaiser点声发射信号关联分维数小于其相邻点，其结论可作为通过波形分析识别Kaiser点的特征。

Abstract

Acoustic emission tests of sandstone specimens under uniaxial compression are carried out; and Kaiser point is determined by parameter method according to the principle of Kaiser effect. First

based on the above testing results

the energy distribution of acoustic emission signals is studied by means of the wavelet packet analysis technique; and regularity of energy distributions for different frequency bands is analyzed. The results show that the energy percentage of dominant frequency band at Kaiser point is significantly higher than other points. Then

relevant fractal dimensions of acoustic emission process are obtained by using G-P algorithm. Results show that the acoustic emission process is of obvious fractal characteristics. And the minimum value of relevant fractal dimension is at Kaiser point. The conclusion can be used to identify the characteristics at Kaiser point by waveform analysis.

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