LIF技术与SIMCA算法在煤矿突水水源识别中的研究  

Research on the Source Identification of Mine Water Inrush Based on LIF Technology and SIMCA Algorithm

作　　者：闫鹏程[1] 周孟然[1] 刘启蒙[2,3] 张开远[1] 何晨阳[1] 

机构地区：[1]安徽理工大学电气与信息工程学院,安徽淮南232001 [2]矿山地质灾害防治与环境保护安徽省重点实验室,安徽淮南232001 [3]安徽理工大学地球与环境学院,安徽淮南232001

出　　处：《光谱学与光谱分析》2016年第1期243-247,共5页Spectroscopy and Spectral Analysis

基　　金：国家"十二五"科技支撑计划重点项目(2013BAK06B01);国家自然科学基金项目(51174258)资助

摘　　要：煤矿突水水源类型的快速识别对于煤矿水害预警防治意义重大。针对传统水化学方法水源识别耗时较长的问题,提出一种基于激光诱导荧光光谱(LIF)技术与簇类的独立软模式(SIMCA)算法的煤矿突水水源快速识别方法。激光诱导荧光光谱技术具有分析速度快、灵敏度高等特点,在激光器的辅助下,荧光光谱仪实时采集荧光光谱,根据水样的荧光光谱即可进行水源类型识别,在数据库完备的情况下,只需几秒即可进行煤矿水源判断,对于煤矿的水害预警以及灾后救援来说意义重大。实验利用405nm激光器发射激光,打入被测水体,得到五种常见突水水样的共100组荧光光谱,对各水样的荧光光谱进行光谱预处理。每种水样使用15组共75组荧光光谱作为预测集,剩余的25组水样的荧光光谱作为测试集。利用主成分分析(PCA)分别对五种水样进行建模,而后依据所建模型进行SIMCA分类。实验发现不同水样的荧光光谱差异明显,经过Gaussian-Filter预处理后的荧光光谱,在主成分数为2,显著性程度α=5%的情况下,利用SIMCA算法进行水样分类,预测集和测试集的正确率皆为100%。Rapid source identification of mine water inrush is of great significance for early warning and prevention in mine water hazard.According to the problem that traditional chemical methods to identify source takes a long time,put forward a method for rapid source identification of mine water inrush with laser induced fluorescence（LIF）technology and soft independent modeling of class analogy（SIMCA）algorithm.Laser induced fluorescence technology has the characteristics of fast analysis,high sensitivity and so on.With the laser assisted,fluorescence spectrums can be collected real-time by the fluorescence spectrometer.According to the fluorescence spectrums,the type of water samples can be identified.If the database is completed,it takes a few seconds for coal mine water source identification,so it is of great significance for early warning and post-disaster relief in coal mine water disaster.The experiment uses 405 nm laser emission laser into the 5kinds of water inrush samples and get 100 groups of fluorescence spectrum,and then put all fluorescence spectrums into preprocessing.Use 15 group spectrums of each water inrush samples,a total of 75 group spectrums,as the prediction set,the rest of 25 groups spectrums as the test set.Using principal component analysis（PCA）to modeling the 5kinds of water samples respectively,and then classify the water samples with SIMCA on the basis of the PCA model.It was found that the fluorescence spectrum are obvious different of different water inrush samples.The fluorescence spectrums after preprocessing of Gaussian-Filter,under the condition of the principal component number is 2and the significant levelα=5%,the accuracy of prediction set and testing set are all 100% with the SIMCA to classify the water inrush samples.

关 键 词：煤矿突水 水源识别 激光诱导荧光光谱 簇类的独立软模式 主成分分析 

分 类 号：O657.3[理学—分析化学]