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通过对瓦斯浓度监测数据预处理方法系统分析,寻找其变化规律。提取样本灰色关联度均值以及95%和97%的样本置信上限,进行预警等级的划分,建立了基于云计算模型的煤矿井下瓦斯预警模型。以宁煤集团矿井瓦斯监测数据为例进行研究,实现了瓦斯浓度的实时预警。
Through systematic analysis of gas concentration monitoring data preprocessing method, looking for the change rule. The average gray correlation degree of samples was extracted, and the sample upper confidence limits of 95% and 97% were obtained. The classification of warning level was carried out, and the gas pre-warning model of coal mine based on cloud computing model was established. Taking Coal Mine Gas Monitoring Data of Ningmei Group as an example, real-time warning of gas concentration is realized.