陈向军, 王兆丰, 王林. 取样过程中损失瓦斯量推算模型研究[J]. 煤矿安全, 2013, 44(9): 31-33,37.
    引用本文: 陈向军, 王兆丰, 王林. 取样过程中损失瓦斯量推算模型研究[J]. 煤矿安全, 2013, 44(9): 31-33,37.
    CHEN Xiang-jun, WANG Zhao-feng, WANG Lin. Research on Gas Loss Quantity Prediction Model in Sampling Process[J]. Safety in Coal Mines, 2013, 44(9): 31-33,37.
    Citation: CHEN Xiang-jun, WANG Zhao-feng, WANG Lin. Research on Gas Loss Quantity Prediction Model in Sampling Process[J]. Safety in Coal Mines, 2013, 44(9): 31-33,37.

    取样过程中损失瓦斯量推算模型研究

    Research on Gas Loss Quantity Prediction Model in Sampling Process

    • 摘要: 根据取样测定煤层瓦斯含量过程中损失瓦斯量难以准确推算的难题,在实验室对吸附平衡绝对瓦斯压力1.5 MPa、实验温度20 ℃条件下的1~3 mm粒径煤样瓦斯解吸过程进行了模拟测试。利用SPSS软件对测试数据进行回归分析,结果表明:指数模型不但能较好描述瓦斯解吸过程,还能准确地推算取样过程中损失的瓦斯量,并建立了取样过程中损失瓦斯量推算模型。根据建立的模型和实验数据,得出暴露时间在 3 min以内时,模型推算的损失瓦斯量误差小于10%,利用模型进行损失瓦斯量推算时,取样时间应控制在3 min以内。利用实验室和现场测试数据分别对建立的模型进行了验证,验证结果表明:利用建立的模型进行推算取样过程中的瓦斯损失量时,误差为1.68%~10.97%,平均为6.98 %,能够满足工程需要。

       

      Abstract: According to the difficult problem that gas loss quantity of coal seam is difficult to accurately calculate during the sampling measurement, the gas desorption process simulation test is made under adsorption equilibrium absolute gas pressure 1.5 MPa, experimental temperature 20 ℃ and 1-3 mm size coal sample in the laboratory. Using SPSS software to regress the test data, the analysis results show that the index model can not only describe gas desorption process, but also can predict gas loss quantity and established gas loss quantity prediction model during sampling. According to the established model and experimental data, it is concluded that the model of the gas loss quantity calculation error is less than 10% when exposure time is less 3 min. Using the model of gas loss quantity calculation, sampling time should be controlled in 3 min. Through validating the model with the data of laboratory and field test, the result shows that the error of the model of the gas loss quantity during sampling is 1.68%-10.97%, and the average error is 6.98%. The result can meet the engineering needs.

       

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