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含瓦斯型煤破坏临界慢化前兆特征研究

发布时间:2018-08-23 09:40
【摘要】:针对煤岩破坏前兆信号的有效性,开展了等效围压下的含瓦斯型煤加载试验,采集了加载破坏过程中的声发射信号,基于临界慢化原理计算了声发射计数-时间序列的方差和自相关系数,分析了煤样破坏的前兆信号.结果表明:等效围压下,含瓦斯煤在压缩破裂过程中,声发射累计计数随时间的响应经历了初始活跃期、稳定增长期、加速增长期和峰后衰减期;不同围压-孔隙压力下煤样压缩破裂声发射特征均存在临界慢化现象,声发射计数序列的方差和自相关系数在煤样破坏前均出现了增大并持续增加的趋势,可以作为煤样破坏的前兆信号.相比声发射累计计数所表征的前兆信号,缩短了前兆信号与破坏点之间的时间差,前兆信号对应的载荷也更接近试样所能承受的最大载荷,更加表明试样确实进入危险破裂阶段.
[Abstract]:Aiming at the validity of the precursor signal of coal and rock failure, the loading test of gas-bearing briquette under equivalent confining pressure is carried out, and the acoustic emission signals during the loading and failure are collected. Based on the critical slowing principle, the variance and autocorrelation coefficient of acoustic emission counting-time series are calculated, and the precursor signals of coal sample destruction are analyzed. The results show that under the equivalent confining pressure, the cumulative acoustic emission (AE) count has experienced the initial active period, the stable growth period, the accelerated growth period and the post-peak attenuation period during the compression rupture of the gas-bearing coal. Under different confining pressure and pore pressure, the characteristics of compression fracture acoustic emission of coal samples have the phenomenon of critical slowing down, and the variance and autocorrelation coefficient of acoustic emission counting series increase and continue to increase before the coal samples are destroyed. It can be used as a precursor signal of coal sample damage. Compared with the precursor signal represented by the cumulative acoustic emission count, the time difference between the precursor signal and the failure point is shortened, and the load corresponding to the precursor signal is closer to the maximum load that the sample can bear. It also shows that the specimen does enter the stage of dangerous rupture.
【作者单位】: 中国矿业大学煤矿瓦斯与火灾防治教育部重点实验室安全工程学院;中国科学院武汉岩土力学研究所;
【基金】:中央高校基本科研业务费专项资金项目(2014ZDPY23) 江苏省研究生培养创新工程项目(KYZZ16_0228) 中国矿业大学优秀创新团队项目(2014ZY001)
【分类号】:TD712;TD32

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1 吴浩;基于临界慢化现象的气候突变前兆信号的研究[D];扬州大学;2014年



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