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岩石破裂失稳声发射监测频段信息识别研究

刘祥鑫, 张艳博, 梁正召, 刘善军

刘祥鑫, 张艳博, 梁正召, 刘善军. 岩石破裂失稳声发射监测频段信息识别研究[J]. 岩土工程学报, 2017, 39(6): 1096-1105. DOI: 10.11779/CJGE201706016
引用本文: 刘祥鑫, 张艳博, 梁正召, 刘善军. 岩石破裂失稳声发射监测频段信息识别研究[J]. 岩土工程学报, 2017, 39(6): 1096-1105. DOI: 10.11779/CJGE201706016
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LIU Xiang-xin, ZHANG Yan-bo, LIANG Zhen-zhao, LIU Shan-jun. Recognition of frequency information in acoustic emission monitoring of rock fracture[J]. Chinese Journal of Geotechnical Engineering, 2017, 39(6): 1096-1105. DOI: 10.11779/CJGE201706016
Citation: LIU Xiang-xin, ZHANG Yan-bo, LIANG Zhen-zhao, LIU Shan-jun. Recognition of frequency information in acoustic emission monitoring of rock fracture[J]. Chinese Journal of Geotechnical Engineering, 2017, 39(6): 1096-1105. DOI: 10.11779/CJGE201706016
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岩石破裂失稳声发射监测频段信息识别研究  English Version

  • 1. 华北理工大学矿业工程学院,河北 唐山063009;
    2. 大连理工大学岩石破裂与失稳研究中心,辽宁 大连 116024;
    3. 东北大学测绘遥感与数字矿山研究所,辽宁 沈阳 110818

基金项目: 国家重点基础研究发展计划（“973”计划）项目（2014CB047100）; 国家自然科学基金项目（51374088,51574102,51604117）
详细信息
    作者简介:

    刘祥鑫(1987- ),男,讲师,主要从事矿山岩石力学教学与研究方面的工作。E-mail: liuxiangxin9@163.com。

  • 中图分类号: TU454

Recognition of frequency information in acoustic emission monitoring of rock fracture

  • 1. School of Mining Engineering, North China University of Science and Technology, Tangshan 063009, China;
    2. State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China;
    3. Institute for Geo-informatics and Digital Mine Research, Northeastern University, Shenyang 110818, China

摘要

    摘要
  • 摘要: 首先对声发射信号进行分频处理,分析岩石损伤破裂演化过程中声发射信号频段分布规律。根据岩石断裂模式与声发射频率存在一定的对应关系,证明了岩石破裂监测中声发射前兆优势频段的存在,进一步构建前兆优势频段的计算方法,确定声发射监测岩石破裂的最优短临预报参数。通过开展花岗岩圆形隧洞模型水平卸荷试验,分析整个过程的声发射信号,寻找前兆优势频段,以此验证方法的可靠性。研究结果表明,水平方向卸荷瞬间,隧洞两壁发生劈裂破坏,频段（31.25~62 kHz）的小波能量占比达73%以上。临近最终破裂,频段（7.8125~15.625 kHz）变能系数由前一刻的0.5突增到15,具有典型的灾变响应特征,可以确定该频段为声发射前兆优势频段。选择作为宏观破裂的短临预报参数,再结合临近最终破裂前声发射主频在频段（90~105 kHz）和（13~20 kHz）所出现的响应突现规律,可以为预测花岗岩圆形隧洞模型的失稳破坏提供预警参量。
    Abstract: The mathematical methods of FFT and wavelet transform are used to deal with the acoustic emission (AE) frequency information of rock fracture firstly. Combined with the spectral distribution of AE signal, the main response spectrum of this lithology in specific form of fracture is selected. The AE precursor advantage spectrum and its calculation method, the most suitable short-term and optimal impending prediction parameters should be optimized, which gives a new way to monitor the disasters of rock mass engineering. In order to prove the validity of this method, the circular tunnel model is used in horizontal unloading tests in laboratory. The results show that the model edge wall around the tunnel is fractured at the moment of horizontal unloading. The energy achieves 73% between 31.25 and 62 kHz, which reflects the properties of rock materials. When it is near the breakdown (TP=2425 s), the changing coefficient of becomes from 0.5 to 15, and it has characteristics of typical disaster response. (7.8125 ~ 15.625 kHz) is the precursor advantage spectrum, and can be used as the macro rupture of short-term and impending prediction parameters combined with the sudden emergence in (90 ~ 105 kHz) and (13 ~ 20kHz) of AE main-frequency. The proposed method may provide new characteristic parameters for disasters monitoring and early warning in rock mass engineering.
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  • 收稿日期:  2016-03-05
  • 发布日期:  2017-06-24

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