矿井瓦斯监测数据趋势预测研究进展

Research Progress on Trend Prediction of Mine Gas Monitoring Data

矿井瓦斯监测数据变化趋势对于分析瓦斯是否异常至关重要,通过回顾和整理国内外研究成果,系统总结了矿井瓦斯时间序列自身所具的趋势性、相关性、周期性及异常性4种特性。归纳出煤与瓦斯突出、炮后瓦斯、局部停风、传感器探头校验以及瓦斯探头故障5种瓦斯异常模式,并综述了灰色系统法、神经网络法、支持向量机以及其他方法在矿井瓦斯预测方面的研究成果。最后总结了矿井瓦斯趋势研究存在的问题和不足,并展望了K线理论的应用前景。

Change trend of mine gas monitoring data is very important to analyze whether the gas is anomaly or not,through sorting out and reviewing the research results at home and abroad,we summarized that the time series of mine gas itself has the tendency,correlation,periodicity and anomalism four characteristics,and also summarized coal and gas outburst,gas after blasting,stopping local ventilation,calibration of sensor probe and sensor probe of gas fault five gas abnormal patterns,and reviewed the grey system,neural network,support vector machine and other methods in prediction of mine gas. Finally,this paper analyzes the mine gas trend of existing problems and shortcomings,and looks forward the K-line theory in the application prospect.