本文關(guān)鍵詞： 煤自燃 CO賦存 BPA D-S理論 預測　出處：《北京科技大學》2017年博士論文　論文類型：學位論文

【摘要】：我國煤炭自燃災害非常嚴重,煤層自燃不僅直接造成資源的浪費,給礦山企業(yè)帶來巨大的經(jīng)濟損失,而且還嚴重威脅企業(yè)人員的生命安全、破壞礦井設(shè)備設(shè)施、危害周邊自然環(huán)境,科學、及時、準確地預測煤層自燃火源對企業(yè)安全生產(chǎn)尤為重要。煤自燃預測的一個關(guān)鍵指標是CO氣體,但如果煤層本身賦存有CO氣體,在開采過程中解吸逸散的CO氣體會干擾礦山煤自燃預測預報工作。本文基于上述問題,選取開灤集團下屬林南倉礦為研究對象,針對該礦煤層是否賦存有CO氣體的爭論,通過現(xiàn)場測試和實驗室實驗證實了煤層賦存有CO氣體,分析了CO氣體賦存成因的影響因素,并在此基礎(chǔ)上提出一種以CO為核心指標,輔以煤溫及C_3H_8、C_2H_4指標氣體,提取監(jiān)測數(shù)據(jù)的信息特征,建立以基本信任分配函數(shù)(BPA)為基礎(chǔ)的煤自燃預測指標體系,運用多源信息融合D-S(Dempster/Shafer)證據(jù)理論實現(xiàn)了賦存CO氣體的煤層自燃預測。1、采用現(xiàn)場鉆孔取氣實驗、煤樣真空解吸實驗并運用協(xié)整理論求證了煤層賦存有原生CO氣體,并從礦井地質(zhì)結(jié)構(gòu)、煤巖大分子結(jié)構(gòu)、煤巖吸附性能、煤巖滲透性能及煤巖孔隙結(jié)構(gòu)特征等方面分析了其對林南倉礦CO氣體賦存成因的影響。2、采用智能煤升溫氧化箱，，有效模擬礦井自然發(fā)火過程,總結(jié)分析了氣體指標參數(shù)與煤溫的對應關(guān)系,選取CO、C_2H_4、C_3H_8為煤自燃預測的標志氣體,并基于CO氣體濃度變化特征將煤自燃前期劃分為賦存氣體解吸期、氧化低危險期、氧化中危險期、氧化高危險期、氧化極高危險期5個階段,利用模糊隸屬度(Fuzzy Membership Function)與IS區(qū)間集兩種方法構(gòu)建了以基本信任分配函數(shù)(BPA)為基礎(chǔ)的煤自燃預測指標體系。3、運用多源信息融合D-S證據(jù)理論,分別就采煤工作面和采空區(qū)進行了煤自燃D-S證據(jù)理論融合預測模擬驗證,并針對多源信息融合中證據(jù)沖突問題,提出了一種基于“相對差異”的證據(jù)沖突度量方法。模擬結(jié)果顯示,本文給出的煤自燃預測方法以特征識別保障了價值信息的有效保留,多源融合增加了預測結(jié)果的準確性,同時為適應井下復雜情況提供了有效的決策依據(jù)。
[Abstract]:Coal spontaneous combustion disaster is very serious in our country. Coal seam spontaneous combustion not only directly causes waste of resources and brings huge economic losses to mining enterprises, but also seriously threatens the safety of enterprise personnel and destroys mine equipment and facilities. It is very important for enterprises to predict the spontaneous combustion source of coal seam in a scientific timely and accurate manner which endangers the surrounding natural environment. A key index of coal spontaneous combustion prediction is CO gas. However, if there is CO gas in the coal seam itself, the CO gas desorbed and dissipated during the mining process will interfere with the prediction and prediction of spontaneous combustion of mine coal. This paper selects Linnancang Mine of Kailuan Group as the research object, aiming at the argument of whether there is CO gas in the coal seam of this mine, and confirms the existence of CO gas in the coal seam by field test and laboratory experiment. Based on the analysis of the factors influencing the occurrence of CO gas, a kind of index gas, which is based on CO as the core index and supplemented by coal temperature and C _ 3H _ 8C _ 2H _ 2H _ 4 index gas, is put forward. The information features of the monitoring data are extracted and the prediction index system of coal spontaneous combustion is established based on the basic trust distribution function (BPA). Based on the evidence theory of multi-source information fusion D-Sine Dempster / Shafer, the prediction of spontaneous combustion of coal seam with CO gas is realized. The coal sample vacuum desorption experiment and cofinishing theory are used to verify the existence of primary CO gas in coal seam, and from the geological structure of coal mine, coal and rock macromolecular structure, coal and rock adsorption performance. The influence of coal and rock permeability and pore structure on the genesis of CO gas in Linancang Mine is analyzed. The intelligent coal heating and oxidation box is used to simulate the spontaneous combustion process effectively. The relationship between the gas index parameters and the coal temperature is summarized and analyzed, and the COG _ Cs _ 2H _ 4 / C _ 3H _ 8 is selected as the mark gas for the prediction of the spontaneous combustion of coal. Based on the change of CO concentration, the coal spontaneous combustion period is divided into five stages: the desorption period of existing gas, the period of low danger of oxidation, the period of middle danger of oxidation, the period of high danger of oxidation, and the period of extreme danger of oxidation. Using fuzzy Membership function) and is interval set, the basic trust assignment function (BPA) is constructed. Based on the prediction index system of coal spontaneous combustion. 3. Based on the D-S evidence theory of multi-source information fusion, this paper simulates the prediction of D-S evidence theory fusion of coal spontaneous combustion in coal mining face and goaf, and aims at the conflict of evidence in multi-source information fusion. A measure method of evidence conflict based on "relative difference" is proposed. The simulation results show that the prediction method of coal spontaneous combustion based on feature recognition ensures the effective retention of value information. Multi-source fusion not only increases the accuracy of prediction results, but also provides an effective decision basis for the complex underground situation.
【學位授予單位】：北京科技大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：TD752.2

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