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为有效分析矿井瓦斯监测数据以拓展监控系统功能,实现工作面瓦斯浓度的有效预警,研究基于多测点实时监测数据关联分析的工作面瓦斯(甲烷)浓度预警方法。通过分析瓦斯实测数据的统计特征,以及利用贝叶斯网络方法分析工作面与其关联监测点瓦斯实测数据构成时间序列的关联特征,确定基于实时监测数据的瓦斯预警指标及其预警阈值,进而分析瓦斯浓度异常情况,实现基于监测数据分析的实时、动态量化预警。实例分析表明,将该方法应用于工作面瓦斯浓度预警,结果显示了瓦斯浓度持续偏大时段反映出的异常情况,符合实际瓦斯浓度变化趋势。
In order to effectively analyze the mine gas monitoring data to expand the monitoring system function and realize the effective early warning of gas concentration in the working face, the gas methane (methane) concentration warning method based on the real-time monitoring data correlation analysis of multiple measuring points was studied. By analyzing the statistical characteristics of gas measured data and using Bayesian network method to analyze the time series correlation characteristics between the face and the gas monitoring data of the associated monitoring points to determine the gas warning index and its early warning threshold based on real-time monitoring data, and then analyze the gas Concentration of abnormal conditions, to achieve real-time, dynamic quantitative warning based on monitoring data analysis. The case study shows that this method is applied to the early warning of gas concentration in the working face. The result shows the anomaly reflected in the continuously high gas concentration period, in line with the trend of the actual gas concentration.