不同水温浸泡后花岗岩声发射特征及其信号识别

发布时间：2018-07-01 11:50

  本文选题：声发射 + 小波包能谱系数　； 参考：《江西理工大学》2015年硕士论文

【摘要】：随着矿山开采的深度增加,高地应力和高地温问题日益凸显,高水温环境下岩体的稳定性是亟待研究解决的课题之一。目前声发射技术已成为矿山地压监测的常用有效手段。论文通过不同水温浸泡后花岗岩声发射特征及其信号识别研究,为高水温环境下岩体稳定性声发射监测技术及工程应用提供理论依据。通过对自然干燥、50度水温和100度水温浸泡后花岗岩进行室内单轴加载声发射试验,获取岩石劣化过程的力学参数、声发射特征参数和声发射信号,运用傅立叶变换、小波包分解分析其频率特性,利用小波包结合分形理论研究声发射信号盒维数与频率对应关系,使用模糊神经网络对不同水温花岗岩声发射信号进行模式识别。主要研究成果如下:1.通过对花岗岩在不同水温浸泡后进行单轴加载声发射试验,分析讨论了岩石破裂过程、应力-应变曲线、变形特征以及声发射参数特性。不同水温岩样均经历了压密闭合、弹性变形、塑性变形及破坏失稳等五个阶段,最大应力值和振铃计数幅度在50度水温下最大,自然干燥下次之,100度水温下最小。2.通过傅立叶变换得到岩石声发射信号的主频范围。50度水温,100度水温花岗岩试件声发射信号的峰值频率主要集中在100k Hz左右,主频范围分布在80~120k Hz区间内;自然干燥下花岗岩试件声发射信号的峰值频率集中在45k Hz左右,主频范围则分布在20~60k Hz左右。3.通过岩样破裂全过程声发射信号的小波包分解,对小波包能谱系数进行分析并提取其频率分布和能量分布。三种水温条件下声发射信号的主要能量都分布在子频带i1、i2、i3、i4、i7和i8,各子频范围的能量分布随加载时间和水温的变化而各有差异。4.结合分形理论对不同水温花岗岩声发射信号小波包进行研究,计算了信号多尺度分形盒维数。自然干燥时主频范围内子信号的分形盒维数在1.4左右,50度水温时主频范围内子信号的分形盒维数在1.6左右,100度水温时,主频范围内子信号的分形盒维数在1.6左右,小波包分解子频带信号的分形盒维数与其频率特征和能量分布具有一致性,能定量地反映声发射信号的特征。5.选取不同水温花岗岩的声发射特征参数、峰值频率、小波包能谱系数以及小波包子信号的分形盒维数建立特征向量,运用模糊神经网络对其进行了模式识别。100度水温,自然干燥花岗岩声发射信号识别率在90%以上,50度水温声发射信号识别率为75%。
[Abstract]:With the increase of mining depth, the problems of high ground stress and high earth temperature become more and more prominent. The stability of rock mass in high water temperature environment is one of the urgent problems to be studied and solved. At present, acoustic emission technology has become a common effective means of mine ground pressure monitoring. In this paper, the acoustic emission characteristics of granite and its signal recognition after immersion at different water temperatures are studied, which provides a theoretical basis for acoustic emission monitoring technology and engineering application of rock mass stability in high water temperature environment. By soaking granite with 50 and 100 degrees of natural drying temperature under uniaxial loading, the mechanical parameters, acoustic emission characteristic parameters and acoustic emission signal of rock degradation process were obtained, and Fourier transform was used. Wavelet packet decomposition analysis of its frequency characteristics, wavelet packet combined with fractal theory to study the acoustic emission signal box dimension and frequency corresponding relationship, using fuzzy neural network for different water temperature granite acoustic emission signal pattern recognition. The main research results are as follows: 1. The rock rupture process, stress-strain curve, deformation characteristics and acoustic emission parameters were analyzed and discussed by means of uniaxial loading acoustic emission test of granite immersed in different water temperature. The rock samples at different water temperatures have undergone five stages: close pressure, elastic deformation, plastic deformation and failure instability. The maximum stress value and ringing counting range are maximum at 50 degrees water temperature, and the minimum of .2. at 100 鈩，

本文编号：2087688