岩石峰值强度前声发射信息多指标及分形维值分析

Multi-indicator and fractal dimensional analysis of acoustic emission information before peak strength of rocks

[目的]探索岩石破坏前的声发射前兆特性可为预测岩石破坏提供依据.[方法]对花岗岩和凝灰岩岩样进行室内单轴压缩实验和多通道声发射测试,对岩样在受力变形直至峰值破裂过程中产生的声发射事件数、b、A(b)、缺震b L、破裂面总面积A(t)、声发射活动标度ΔF、声发射活动度S,以及声发射能量和事件源空间位置的分形特性等参数和指标进行分析.[结果]通过实验与分析得到了两个结果:1)b和缺震b L在岩样破坏前明显下降,出现低值异常;A(b)、声发射活动度S、声发射活动标度ΔF和破裂面总面积A(t)在岩样破坏前突然上升,出现高值异常.2)加载过程中声发射能量释放和源空间位置演化具有很好的分形特性,且空间时序比能量时序的分形特性更明显.[结论]本文引入了综合考虑“时空强”的参数和物理意义明确的统计学指标,可以很好地表征岩石破坏前的声发射特性,可为进一步对岩石破坏预测研究提供依据.

[Objective]Exploring the acoustic emission precursor properties before rock damage can provide a basis for predicting rock damage.[Methods]Indoor uniaxial compression tests and multi-channel acoustic emission tests were conducted on granite and tuff samples to analyze the number of acoustic emission events,b,A(b),lack of seismicity b_(L),total area of rupture surface A(t),acoustic emission activity scaleΔF,acoustic emission activity S,and fractal characterization of acoustic energy and spatial location of the event source during the deformation of rock samples in force up to the peak fracture process.[Results]Two results were obtained through experimentation and analysis::(1)The b and lack of seismic b L decreased significantly before the destruction of the rock samples,and low value anomalies appeared;the A(b),the acoustic emission activity S,the acoustic emission activity scaleΔF,and the total area of the rupture surface A(t)increased suddenly before the destruction of the rock samples,and high value anomalies appeared.(2)The acoustic emission energy release and source spatial position evolution during the loading process have good fractal characteristics,and the fractal characteristics of the spatial time series are more obvious than those of the energy time series.[Conclusions]This paper introduces a comprehensive consideration of“time-space-intensity”parameters and statistically significant indicators with clear physical meanings,which can effectively characterize the acoustic emission characteristics prior to rock failure,thus providing a solid foundation for further research on rock failure prediction.