基于Piper-PCA-Fisher的矿井突出水源判别模型构建及应用  

Construction and application of Piper-PCA-Fisher based model in identification of mine water inrush source

作　　者：孙延辉 胡文博 马红林 王历民 杜华 李世涛 Sun Yanhui;Hu Wenbo;Ma Honglin;Wang Liming;Du Hua;Li Shitao(New Shanghai No.1 Coal Mine,Inner Mongolia Shanghaimiao Mining Co.,Ltd.,Erdos Inner Mongolia 016200,China)

机构地区：[1]内蒙古上海庙矿业有限责任公司新上海一号煤矿,内蒙古鄂尔多斯016200

出　　处：《化工矿物与加工》2023年第9期52-58,80,共8页Industrial Minerals & Processing

摘　　要：突水水源的高效准确判别是防治突水事故的关键,为提高矿井突水水源判别的可靠性,以临涣矿区水样数据为例,提出了一种基于Piper三线图、主成分分析(Principal Component Analysis,PCA)与Fisher判别法的矿井突水水源判别模型。将6类化学离子实测浓度作为突水水源判别指标,通过确定评价集与4类水源中心的距离进行样本归类判别。研究结果表明:采用Piper三线图可剔除异常样本,最终确定以37组典型水样作为训练样本;利用主成分分析对判别指标进行降维,发现前3项主成分覆盖了原有指标信息的91.636%,能够有效表征样本水化学特征;利用Piper-PCA-Fisher判别模型回判37组训练样本并预测15组待测样本,回判准确率及预测正确率均为100%。Piper-PCA-Fisher判别模型可减弱指标间的关联度,在水样数据有限的情况下,可获得良好的判别效果。The efficient and accurate identification of water inrush sources is a critical step to prevent mines from water inrush accidents.In order to improve the reliability of identification of mine water inrush source,a mine water inrush source identification model based on Piper trilinear diagram,Principal Component Analysis(PCA),and Fisher identification method was presented with the data of water sample taken from Linhuan mining area as a study case.Using the concentration tested for six categories of chemical ions as the identification index for water inrush sources,sample classification and identification were carried out by determining the distance between the evaluation set and the center of the four categories of water sources.The research results indicate that the Piper trilinear diagram can be utilized to exclude abnormal samples,and ultimately 37 sets of typical water samples were chosen to be training samples.Principal component analysis was adopted to reduce the dimensionality of identification index.It can be found that the former three principal components presented 91.636%coverage of the original index information,which made the hydro-chemical property of the sample be characterized efficiently.The Piper-PCA-Fisher model was applied to back identify 37 sets of training samples and predict 15 sets of samples to be tested,and the accuracy of both back identification and prediction was 100%.The Piper-PCA-Fisher identification model helps to weaken the correlation between the indexes.The sound identification effects in case of limited availability of water sample data can be acquired.

关 键 词：矿井突水 水源判别 Piper三线图 主成分分析 Fisher判别法 降维 

分 类 号：TD745[矿业工程—矿井通风与安全]