基于雪崩动力学的声发射预警模型在煤与瓦斯突出监测与预报的应用

Application of Acoustic Emission Alerting Model Based on Avalanche Dynamics in Coal and Gas Outburst Monitoring and Forecasting

摘要: 合理的声发射预警指标及预警模型是利用声发射监测技术进行突出危险性预测的依据。本文对现场实测微震监测数据进行对比分析，结果表明：微震与声发射监测数据变化规律相似，但单位时间内声发射装置接收到的事件数远比微震装置接受到的事件数多，更能良好反应工作面前方突出危险。瓦斯超标前期的任意时间区间声发射能量概率密度函数满足幂律分布，拟合表明区间的临界指数随着离瓦斯超标区域的距离的靠近呈减小趋势。临界幂值分布通过最大似然的方法量化进行危险性评估，当临界幂值曲线所表征的临界值向下移动，甚至急剧下滑，曲线在大能量区间分布较稳定，此时预示着工作面具有突出危险性，数据离散性增加，临界幂值越大。

Abstract: Reasonable sound emission warning indicators and early warning models are the basis for using the acoustic emission monitoring technology to highlight risk prediction. The field observations of microseismic monitoring data are compared and analyzed. The results show that the microseismic and acoustic emission monitoring data have similar variation rules, but the number of events received by the acoustic emission device per unit time is much more than the number of events received by the microseismic device, and the response to danger in front of the face is better. The probability density function of acoustic emission energy at any time interval before the gas exceeds the limit satisfies the power law distribution. Fitting shows that the critical index of the interval decreases with the distance from the gas exceeding the standard area. The critical power value distribution is quantified by the maximum likelihood method for risk assessment. When the critical value represented by the critical power value curve moves downwards, and even declines sharply, the distribution of the curve with large energy is stable, indicating that the working surface has highlighted the danger, increased the discrepancies of the data, and increased the critical power value.