Early-warning evaluation and warning of rock burst using acoustic emission characteristics of coal sample failure
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摘要:
冲击地压作为深部煤矿开采中最常见的煤岩动力灾害，严重影响煤炭资源安全高效开采。精准及时的预测预报是冲击地压防治的关键。为研究煤岩体冲击前兆信息特征，建立高效精准的动态预测模型，通过对冲击倾向性煤样进行三轴压缩试验，获取煤样破坏过程声发射特征参数，选取典型冲击矿井工作面微震参数监测值，与实验室所得声发射参数进行对比，分析实验室和工程尺度下的声发射与微震参数特征之间的相似性，建立两者之间冲击声学信息的表征关系。结果表明，煤样压缩过程中声发射累计能量的“阶梯状”增长与大能量矿震事件发生前的“缺震”现象都揭示了煤岩体能量的孕育过程。同一能量指标在不同尺度下对大能量事件的发生具有相同的演化趋势，经量化后可作为冲击地压危险性预警指标。继而选取影响工作面冲击地压发生的静态因素与应力动态因素，结合所得微震参数指标分别赋予动态权重，并引入贝叶斯概率进行修正，构建冲击地压动−静态协同综合评价预警模型。利用该模型对河南某冲击矿井工作面危险性进行评价预警，获得优于传统评价模型的预警结果，展现了该模型的工程适用性与准确性。
Abstract:As the most common dynamic disaster of coal rock in deep coal mining, rock burst seriously affects the safe and efficient mining of coal resources. Accurate and timely to predict the rock burst is the best way to control and prevent it. In order to study the precursory information characteristics of coal rock impact to establish an efficient and accurate dynamic prediction model. The triaxial compression test of coal bursting liability performed to get the acoustic emission characteristic parameters of coal failure process, meanwhile the monitoring values of microseismic parameters of typical impact mine face were selected and compared with the AE parameters obtained in the laboratory, then based on the similarity of them, the relationship between laboratory-scale and engineering-scale impact acoustic information representation had been built. It shows the “stepwise” increase of accumulated AE energy during coal sample compression and the “lack of earthquake” phenomenon before the occurrence of large energy seismic events have a good correlation, both of them could be used to revealed the energy breeding process of coal and rock mass. The same energy index has the same evolutionary trend for the occurrence of large energy events at different scales, and it can be used as an early warning index of rock burst risk after quantification. In addition, the static factors and stress dynamic factors affecting the occurrence of rock burst in working face are selected, and the dynamic weights are given respectively by combining the microseismic parameters obtained, which modified by using the Bayesian probability, then a static cooperative comprehensive evaluation and early warning model of rock burst is constructed. Furthermore, the model is used to evaluate and warn the danger of a mining face in Henan Province, and the results are better than those of the traditional evaluation model, which shows the engineering applicability and accuracy of the model.
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图 2 自动线切割制备仪器及制备完成的煤样试件
Figure 2. Automatic wire cutting preparation instrument and finished coal sample
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图 5 试件1应力、声发射参数与时间关系
Figure 5. Relationship between stress, acoustic emission parameters and time of test piece 1
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图 6 试件2应力、声发射参数与时间关系
Figure 6. Relationship between stress, acoustic emission parameters and time of test piece 2
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图 7 试件3应力、声发射参数与时间关系
Figure 7. Relationship between stress, acoustic emission parameters and time of test piece 3
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图 12 工作面第一季度单日微震频次与能量
Figure 12. Single-day microseismic frequency and energy of the working face in the first quarter
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图 13 工作面第二季度单日微震频次与能量
Figure 13. Single-day microseismic frequency and energy of the working face in the second quarter
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图 15 工作面单日最大能量计算 b 值演化趋势
Figure 15. Evolution trend of b value calculated for the maximum energy of working face on a day
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图 16 工作面单日最大能量计算A(b)值演化趋势
Figure 16. Evolution trend of A(b) value calculated for the maximum energy of working face on a day
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图 17 工作面单日最大能量计算EEM值演化趋势
Figure 17. Evolution trend of EEM value calculated for the maximum energy of working face on a day
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图 18 煤样破坏前声发射能量“阶梯状”增长
Figure 18. “Stepwise” growth of acoustic emission energy before coal sample destruction
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图 19 工作面微震监测中“缺震”现象
Figure 19. “Lack of earthquake” phenomenon in microseismic monitoring of working face
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图 20 冲击地压综合危险等级评价流程
Figure 20. Comprehensive risk grade evaluation process of rock burst
表 1 2019年强矿震事件发生日期及能量
Table 1 Occurrence date and energy of strong ore earthquake events in 2019
事件
编号日期 能量/J 事件
编号日期 能量/J 1* 01−03 9.2×105 6* 06−14 5.2×105 2* 01−13 1.6×106 7* 07−09 1.7×107 3* 02−26 7.8×105 8* 08−05 5.2×105 4* 03−25 1.3×106 09* 10−08 5.7×105 5* 04−24 6.5×105 10* 12−01 7.9×105 
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表 2 静态指标Wt危险分级
Table 2 Static index Wt hazard classification
等级 无 弱冲击 中等冲击 强冲击 Wt [0～0.25] (0.25～0.5] (0.5～0.75] (0.75～1]
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表 3 应力指数St危险分级
Table 3 Stress index St hazard classification
等级 无 弱冲击 中等冲击 强冲击 St [0～0.25] (0.25～0.5] (0.5～0.75] (0.75～1]
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表 4 微震指标Wij危险分级
Table 4 Risk classification of microseismic index Wij
等级 无 弱冲击 中等冲击 强冲击 Wij [0～0.25] (0.25～0.5] (0.5～0.75] (0.75～1]
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表 5 冲击地压综合指标Z危险分级
Table 5 Hazard classification of comprehensive index Z of rock burst
等级 无 弱 中等 强 Z [0～0.25] (0.25～0.5] (0.5～0.75] (0.75～1]
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表 6 综合预警模型工程应用测试结果
Table 6 Comprehensive early warning model engineering application test results
日期
(月−日)Wt
危险性St
危险性Wij
危险性综合模型
预警结果综合模型
准确性01-03 中 弱 弱 弱 是 01-13 弱 弱 中 弱 是 01-18 弱 弱 弱 弱 是 02-03 中 中 弱 弱 是 02-04 弱 弱 弱 弱 是 02-06 弱 弱 弱 弱 是 02-08 弱 弱 弱 弱 是 02-26 中 中 弱 弱 是 03-25 弱 中 中 中 否
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表 7 冲击地压传统评价方法优缺点对比
Table 7 Comparison of advantages and disadvantages of traditional evaluation methods for rock burst
评价方法 优点 缺点 综合指数法 方法简单，指标设定灵活，可将定性数据定量化分析 过度依赖评定指标，在复杂矿井及开采动态过程中准确性较低 模糊综合评价法 将定性评价转化为定量评价，可对多因素非确定性问题进行综合评价 计算复杂，指标较多时权向量和模糊矩阵难以匹配，对指标权重的确定主观性较强 层次分析法 定性与定量相结合，适用于多因素多准则等难以量化处理的系统评价 准确度依赖人的定性主观判断，综合考虑冲击地压多因素影响指标时权重难以确定 突变级数法 无需确定各指标具体权重值，减少权重数值误差带来的影响 准确度依赖于指标相对重要度评定，指标排序问题受主观影响较大
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表 8 不同模型评价结果对比
Table 8 Comparison of evaluation results of different models
日期
（月−日）综合
指数法模糊综合
评价法层次
分析法突变
级数法综合评价
预警模型01-03 弱 弱 弱 弱 弱 01-13 弱 弱 弱 弱 弱 01-18 无 弱 弱 弱 弱 02-03 中 弱 中 弱 弱 02-04 弱 弱 弱 弱 弱 02-06 弱 弱 弱 弱 弱 02-08 弱 弱 弱 弱 弱 02-26 弱 弱 弱 弱 弱 03-25 中 中 弱 中 中
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