武甲煤矿掘进工作面煤与瓦斯突出危险预警及可视化研究

发布时间：2018-05-17 13:17

本文选题：煤与瓦斯突出 + 预测敏感指标　；参考：《中国矿业大学》2017年硕士论文

【摘要】：随着煤矿开采深度的不断增加,煤与瓦斯突出等煤岩动力灾害的威胁日趋加剧,这严重制约了煤矿的安全生产。因此,提高煤与瓦斯突出危险预警的准确性和效率已逐渐成为煤矿安全生产亟待解决的重大技术问题之一。由于不同煤层赋存特性的影响,常用突出预测指标在不同矿区有时突出敏感性不强,极大地影响了突出预测的准确性。基于此,本文对试验矿井突出预测指标进行了分析。研究了不同指标的敏感性及其临界值,进行了突出指标的超前预测和可视化分析。论文主要成果如下:本文针对突出矿井煤与瓦斯突出预测敏感指标及临界值的确定问题,通过模糊数学与概率统计相结合,建立了各个预测指标的敏感度函数,计算了不同预测指标的敏感性,得到了1maxK作为武甲煤矿突出预测敏感性指标;基于突出指标实测数据利用“三率法”分析确定了敏感预测指标的临界值。建立了煤与瓦斯突出的优化灰色预测模型,经验证优化后的灰色预测模型在煤与瓦斯突出超前预测的准确率得到了提升;建立了模糊物元煤与瓦斯突出预警模型,具有突出危险“无、轻、中、重”4级预警等级;利用3D MAX软件建立了煤与瓦斯突出可视化三维模型,实现了掘进工作面煤与瓦斯突出危险的可视化预测,并进行了验证应用。本研究对综合判断掘进工作面安全状况及前方的潜在危险性,减少瓦斯灾害事故的发生,保障矿井安全生产具有重要的实际意义。
[Abstract]:With the increasing depth of coal mining, the threat of coal and gas outburst and other coal-rock dynamic disasters is becoming more and more serious, which seriously restricts the safety of coal production. Therefore, improving the accuracy and efficiency of coal and gas outburst warning has gradually become one of the important technical problems to be solved urgently. Due to the influence of the occurrence characteristics of different coal seams, the commonly used outburst prediction indexes are not sensitive to outburst in different mining areas, which greatly affects the accuracy of outburst prediction. Based on this, this paper analyzes the outburst prediction index of experimental mine. The sensitivity and critical value of different indexes are studied, and the advanced prediction and visual analysis of prominent indicators are carried out. The main achievements are as follows: aiming at the problem of determining sensitive index and critical value of outburst prediction of coal and gas outburst, the sensitivity function of each prediction index is established by combining fuzzy mathematics with probability statistics. The sensitivity of different prediction indexes is calculated and the critical value of sensitive prediction index is determined by "three rate method" analysis based on the measured data of the outburst of Wujia Coal Mine, which is regarded as the sensitivity index for outburst prediction by 1maxK. The optimized grey prediction model of coal and gas outburst is established, and the accuracy of the optimized grey prediction model in coal and gas outburst prediction is improved, and the fuzzy-matter coal and gas outburst warning model is established. It has four warning grades of "no, light, medium and heavy", and establishes the visual 3D model of coal and gas outburst by using 3D MAX software, realizes the visual prediction of coal and gas outburst danger in tunneling face, and verifies the application. This study is of great practical significance in synthetically judging the safety situation and potential danger in front of heading face, reducing the occurrence of gas disaster accident and ensuring mine safety production.
【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD713

【参考文献】