硫化矿石自燃倾向性分级的云模型及其应用  

Cloud model and its application of classifying spontaneous combustion tendency of sulfide ores

作　　者：阳富强[1] 朱伟方[1] 刘晓霞[1] 

机构地区：[1]福州大学环境与资源学院,福建福州350116

出　　处：《自然灾害学报》2018年第1期208-214,共7页Journal of Natural Disasters

基　　金：国家自然科学基金(51741402;51304051);福建省自然科学基金(2016J01224);福建省高校杰出青年科研人才培养计划(83016018);福州大学贵重仪器设备开放测试基金(2018T012)~~

摘　　要：为了科学判定高硫矿床开采中硫化矿石的自燃倾向性等级,选取了吸氧速度常数、自热点、着火点3个测定指标,建立了基于熵权法和云模型的硫化矿石自燃倾向性分级模型。将硫化矿石自燃倾向性测定指标及分级标准转化为正态云分级标准,采用熵权法对各个指标的实际测试值进行指标赋权;以模糊子集B的最大隶属度原则为依据,判定各个矿样的自燃倾向性等级。利用国内某典型矿山的10组代表性矿样对该模型的可行性进行检验,所得分类结果与多因素综合比较法的判定结果相一致。该模型能够提高矿样自燃倾向性等级划分的准确性,并且为有效指导高硫矿山自燃火灾的防治工作提供了一种新方法。In order to determine the grade of spontaneous combustion tendency of sulfide ores in sulfur-rich ore deposits scientifically, three determination indexes were selected, including the oxygen absorption rate on average, self-heating point, and ignition point. The classification model of spontaneous combustion tendency of sulfide ores was established based on entropy weight and the cloud model. The determination index of spontaneous combustion tendency of sulfide ores and the classification standard were transformed into normal cloud classification standard. The index weight of actual test value for each index were empowered by entropy method. The level of spontaneous combustion tendency of each sample was determined based on the principle of maximum membership degree of fuzzy subset B. The feasibility of this model was confirmed by using 10 representative samples from a typical mine in China. The classification results were consistent with that obtained by the method of multi-factor comprehensive evaluation. The model can increase the accuracy effectively in determining the level of spontaneous combustion tendency of sulfide ores, so it provides a new method for controlling the spontaneous fire of sulfur-rich mines.

关 键 词：硫化矿石 自燃倾向性等级 熵权法 云模型 

分 类 号：X925[环境科学与工程—安全科学]