本文選題：煤炭地下氣化 + 選址決策��； 參考：《中國(guó)礦業(yè)大學(xué)》2017年碩士論文

【摘要】：煤炭地下氣化技術(shù)是一種既能實(shí)現(xiàn)煤炭資源綠色、安全、高效開(kāi)采,又能通過(guò)改變煤氣后續(xù)利用方式實(shí)現(xiàn)煤氣資源潔凈與綜合利用的煤炭開(kāi)采新技術(shù)�？茖W(xué)選址是煤炭地下氣化技術(shù)中重要一環(huán),直接影響到后續(xù)氣化爐的建立,產(chǎn)氣的穩(wěn)定性和優(yōu)劣性,以及最終的經(jīng)濟(jì)效益和環(huán)境效益。因此,需要建立一個(gè)行之有效的煤炭地下氣化選址決策系統(tǒng)。本文引入BP人工神經(jīng)網(wǎng)絡(luò),綜合采用文獻(xiàn)調(diào)研、理論分析、數(shù)值模擬以及仿真應(yīng)用相結(jié)合的研究方法,提出可行的選址模型,取得了如下創(chuàng)新性成果:(1)本文著重對(duì)煤炭地下氣化可行性的資源條件影響因素進(jìn)行了全面分析,如地質(zhì)構(gòu)造、水文地質(zhì)條件、煤層賦存條件、煤質(zhì)等,選取了14項(xiàng)因素作為煤炭地下氣化項(xiàng)目可行性評(píng)價(jià)指標(biāo),并根據(jù)地下氣化項(xiàng)目的特點(diǎn),確定了各評(píng)價(jià)指標(biāo)的合理取值范圍,建立煤炭地下氣化選址評(píng)估體系。(2)通過(guò)對(duì)神經(jīng)網(wǎng)絡(luò)的分析,本文首次將BP人工神經(jīng)網(wǎng)絡(luò)引入煤炭地下氣化選址決策中,設(shè)計(jì)出基于標(biāo)準(zhǔn)BP神經(jīng)網(wǎng)絡(luò)和LM-BP神經(jīng)網(wǎng)絡(luò)的煤炭地下氣化選址評(píng)估模型的網(wǎng)絡(luò)結(jié)構(gòu)。利用Matlab,對(duì)優(yōu)化的LM-BP神經(jīng)網(wǎng)絡(luò)與標(biāo)準(zhǔn)BP神經(jīng)網(wǎng)絡(luò)進(jìn)行對(duì)比實(shí)驗(yàn)和分析,尋求出最優(yōu)的網(wǎng)絡(luò)相關(guān)參數(shù)。實(shí)驗(yàn)證明,優(yōu)化的LM-BP神經(jīng)網(wǎng)絡(luò)具有更好的性能。對(duì)三個(gè)樣本案例進(jìn)行仿真應(yīng)用,仿真結(jié)果表明,基于LM-BP神經(jīng)網(wǎng)絡(luò)的煤炭地下氣化評(píng)估模型評(píng)估準(zhǔn)確可靠,能夠指導(dǎo)煤炭地下氣化的選址評(píng)估。對(duì)煤炭地下氣化發(fā)展有重要意義。(3)本文在對(duì)仿真實(shí)例詳細(xì)分析的同時(shí),對(duì)BP人工神經(jīng)網(wǎng)絡(luò)在煤炭地下氣化中的應(yīng)用進(jìn)行兩方面的擴(kuò)展,即可根據(jù)煤氣組分預(yù)測(cè)熱值和根據(jù)氣化日期預(yù)測(cè)熱值,具有進(jìn)一步研究的價(jià)值。
[Abstract]:Underground coal gasification technology is a new coal mining technology which can not only realize green, safe and efficient mining of coal resources, but also realize clean and comprehensive utilization of gas resources by changing the way of gas utilization. Scientific location selection is an important part of underground coal gasification technology, which directly affects the establishment of subsequent gasifier, the stability and quality of gas production, as well as the final economic and environmental benefits. Therefore, it is necessary to establish an effective decision system for underground coal gasification location. In this paper, BP artificial neural network is introduced, and a feasible location model is put forward by combining the research methods of literature investigation, theoretical analysis, numerical simulation and simulation application. In this paper, the factors affecting the feasibility of underground coal gasification are analyzed, such as geological structure, hydrogeological conditions, coal seam occurrence conditions, coal quality, etc. This paper selects 14 factors as the feasibility evaluation index of underground coal gasification project, and according to the characteristics of underground gasification project, determines the reasonable value range of each evaluation index. Based on the analysis of neural network, BP artificial neural network is introduced into the decision of underground coal gasification site selection for the first time. The network structure of coal underground gasification location evaluation model based on standard BP neural network and LM-BP neural network is designed. The optimized LM-BP neural network and the standard BP neural network are compared and analyzed by Matlab, and the optimal network parameters are found out. Experiments show that the optimized LM-BP neural network has better performance. The simulation results show that the evaluation model of underground coal gasification based on LM-BP neural network is accurate and reliable and can guide the evaluation of underground coal gasification location. In this paper, the application of BP artificial neural network in underground coal gasification is extended in two aspects, while the simulation example is analyzed in detail. The calorific value can be predicted according to the composition of gas and the date of gasification, which has the value of further study.
【學(xué)位授予單位】：中國(guó)礦業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TD84

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