基于熵权-模糊可变集理论的煤矿井突水水源识别

Identification of water inrush source from coalfield based on entropy weight-fuzzy variable set theory

在阐述熵权法和模糊可变集理论的基础上,针对平顶山煤田首山一矿和十三矿4个充水水源中所提取的23个水样,构建了识别矿井突水水源的数学模型,并利用该模型对8个水样进行了来源识别。结果表明:各类充水水源中Ka^++Na^+,Ca^(2+),Mg^(2+),Cl^-,SO_4^(2-)和HCO_3^-等6项化学指标值在区间特定值附近出现的概率比较高,可用模糊可变集理论识别突水水源;熵权法计算的Ka^++Na^+和Ca^(2+)权重值分别为0.270 8和0.371 3,远高于其他指标的权重值,且其权重值之和占64.21%,说明两项指标在矿井突水水源识别中起主要作用;8组水样识别时,除水样8识别结果不符合实际外,其余均与实际类型相符,其准确率为87.5%;对于平顶山煤田来说,识别模型中的优化准则参数a选取2时,熵权-模糊可变集模型识别突水水源的准确性更高;应依据丰富的时空水质检测数据来建立模型并及时应用新的资料予以修正,以保证所建识别模型符合实际并与时俱进。

Based on the entropy weight method and fuzzy variable set theory,23 water samples were extracted from the four water sources at Shoushan mine and the thirteenth mine in Pingdingshan coalfield,a mathematical model of identification of mine water inrush was built,and the sources of 8 water samples were identified using the model.The results show that the probability of the 6 chemical indexes,namely Ka^＋＋Na^＋,Ca^2＋,Mg^2＋,Cl^-,SO4^（2-） and HCO3^-,appearing near the Interval specific value is relatively high; the weights of Ka^＋＋Na＋and Ca^2＋ were 0. 270 8 and 0. 371 3with entropy weight method,much higher than other index weight,and the sum of weights accounted for 64.21%,indicating the major role in the mine water inrush identification; the identification results of 7 groups of water samples were consistent with the actual type except the water sample 8,accuracy rate reaching 87.5%; for Pingdingshan coalfield,selecting the optimization criterion of parameter a = 2 in the identification model,the accuracy of entropy weight-varia-ble fuzzy set model to identify the source of water inrush is higher; the model should be established on the basis of abundant spatial and temporal water quality data,and improved using the new information to ensure the identified model conforming to the reality and keeping pace with the times.