摘要:
煤尘爆炸因其强大的破坏力和广泛的致灾范围成为煤矿最严重的事故之一。为分析瞬态爆炸反应过程中多因素耦合效应对煤尘爆炸强度的影响,采用Box-Behnken试验设计方法共进行了45组20L球形爆炸试验,观察了煤尘浓度(A)、煤尘粒径(B)、煤挥发分(C)、点火能量(D)和点火延迟(E)5个因素耦合作用下煤尘爆炸强度的宏观特征。通过测量压力变化来监控爆炸过程,并从压力-时间曲线确定最大爆炸压力(响应值Y1)及其上升速率(响应值Y2)。使用Design-Expert软件分析实验结果,以建立响应值Y1和Y2的二次回归模型。结果表明,在方差分析(ANOVA)中,Y1和Y2的决定系数(R)分别为0.9771和0.9258,表明模型和实验数据之间的良好拟合。在模型中,对煤尘最大爆炸压力(Y1)影响最大的单因素是点火能量和点火延迟,对最大爆炸压力上升速率(Y2)影响最大的单因素是煤尘粒径和点火延迟。影响Y1的显著双因素交互作用是AB、AD、AE、BC、CD、CE和DE,而影响Y2的显著双因素交互作用是AE、BC、BE、CE和DE。其中,点火延迟在响应值Y1和Y2中起决定性作用。研究结果可为井下煤尘防爆工作提供理论基础。
Abstract:
Coal dust explosion has become one of the most serious accidents in underground coal mines due to its powerful destructive force and extensive damage range. Using the Box-Behnken experimental design method, the influence of multi-factor coupling effects on the intensity of coal dust explosion during the transient explosion reaction process was studied. A total of 45 groups of 20L spherical explosion tests were conducted, observing the macroscopic characteristics of the intensity of coal dust explosion under the coupling effects of five factors: coal dust concentration (A), coal dust particle size (B), coal volatile matter (C), ignition energy (D), and ignition delay (E). The explosion process was monitored by measuring pressure changes, and the maximum explosion pressure (response value Y1) and the maximum explosion pressure rise rate (response value Y2) were determined from the pressure-time curve. The Design-Expert software was used to analyze the experimental results to establish a quadratic regression model for response values Y1 and Y2. The results show that in the variance analysis (ANOVA), the coefficient of determination (R) for Y1 and Y2 is 0.9771 and 0.9258, respectively, indicating a good fit between the model and experimental data. The single factor that has the greatest influence on the maximum explosion pressure (Y1) is ignition energy and ignition delay, and the single factor that has the greatest influence on the rise rate of the maximum explosion pressure (Y2) is coal dust particle size and ignition delay. In the quadratic regression model, the significant two-factor interaction affecting Y1 are AB, AD, AE, BC, CD, CE, and DE, while significant two-factor interaction affecting Y2 are AE, BC, BE, CE, and DE. Among them, ignition delay plays a decisive role in response values Y1 and Y2.The research results can provide a theoretical basis for dust explosion prevention work in underground coal mines.