采掘工作面瓦斯异常涌出灰色预警模型的建立和应用

Establishment of Gray Early Warning Model for Gas Abnormal Emission at Extracting Coal Face and Its Application

摘要: 依据灰色系统理论，选取现场瓦斯异常涌出较为典型的4个致因指标，建立了工作面瓦斯异常涌出的灰色预警模型，计算了各样本指标的权系数以及所选取样本集的综合权系数，根据模型测度对工作面瓦斯涌出情况进行了预测。预测结果与瓦斯突出理论以及现场实际相一致，验证了该模型在采掘工作面瓦斯异常涌出预测应用中的可行性。
- 瓦斯异常涌出 /
- 灰色预警 /
- 权系数 /
- 模型测度 /
- 聚类分析
Abstract: Based on the gray system theory, the gray early warning model of gas abnormal emission at extracting coal face is established by selecting the more typical four causes of abnormal gas emission at scene. And index weights of each sample and the synthetic weight coefficient of selected sample has been calculated to predict gas emission situation at face according to model measure. The theory prediction and the actual site are consistent, and the model has been verified in gas abnormal emission forecasting.
- abnormal gas emission /
- gray early-warning /
- weight coefficient /
- model measure /
- cluster analysis

[1]	AQ1018-2006矿井瓦斯涌出量预测方法[S].
[2]	周世宁,林柏泉.煤层瓦斯赋存与流动理论[M].北京：煤炭工业出版社,1999.
[3]	郭德勇,李念友，裴大文，等.煤与瓦斯突出预测灰色理论-神经网络方法[J]. 北京科技大学学报,2007(4)：354-357.
[4]	景国勋,张强，周爱桃，等.基于灰色系统理论的煤与瓦斯突出预测[J]. 中国安全科学学报,2004(8)：18-21.
[5]	贾晓亮．煤层瓦斯含量测定方法及误差分析[J]．煤矿开采，2009(2)：93.
[6]	聂韧,赵旭生.掘进工作面瓦斯涌出动态指标预测突出危险性的探讨[J]. 矿业安全与环保,2004(8)：36-38.
[7]	吴强.基于神经网络的煤与瓦斯突出预测模型[J].中国安全科学学报,2001(8)：69-72.
[8]	康宇,王兆丰，刘军，等.多元线性回归在瓦斯抽放量预测中的应用[J]. 煤炭工程,2012(3):59-61.