基于多方法耦合的矿井突水水源识别模型研究

为快速准确地判别矿井突水水源,减少矿井突水事故带来的危害,以保德矿为例,选取Ca2+、Mg2+、Na++K+、SO2-4、Cl-、HCO-3共6种水化学指标作为判别指标,通过分析各含水层水化学特征,确定了各含水层代表水样,以此为基础建立了耦合主成分分析-离群值检验-回归填补法-贝叶斯判别法的矿井突水水源判别模型,并将模...

Identification Model of Water Inrush Source Based on Piper-PCA-OT-Regression-Bayes

In order to identify the water source of mine water inrush quickly and accurately, and reduce the harm caused by mine water inrush, Baode mine was taked as an example, Ca2+、Mg2+、Na++K+、SO42－、Cl-、HCO3- were selected as the discrimination indexes. Through The representative water samples of each aquifer Were determined by analyzed the chemical characteristics of water samples. And then, the coupled Principal Component Analysis (PCA) - Outlier Tests (OT) - Regression - Bayes model were used to identify the water source of Baode mine. The results show that: the water quality types of the Goaf, Permian sandstone aquifer, Carboniferous sandstone aquifer and Ordovician limestone aquifer in Baode mine were HCO3-Ca.Na.Mg, HCO3-Na, HCO3-Na, HCO3-Ca. The main components of Baode mine water samples are Ca2+、Mg2+、Na++K+、SO42－, which can be used as comprehensive indicators to reflect the original water sample data information of Baode mine. The outliers in the tested water samples were determined and corrected by Outliers Test and Regression model. Compared the results of before and after data correction, the accuracy after correction was 95%, and the accuracy was significantly improved, which can accurately and efficiently identify water inrush source.