煤层地质条件模糊综合评价在中国的应用毕业课程设计外文文献翻译

Fuzzy evaluation on geological conditions of coal seam in ChinaZhang Dongsheng, Zhang Xianchen & Yan XuefengChina University of Mining & Technology, Xuzhou, Jiangsu, P. R. ChinaDAbstract The geological conditions of coal seam are evaluated quantitatively by using fuzzy method and from pointview of coal mining. According to the evaluation results, decision-making on mining techniques, mining programming and design, production management can be carried out effectively. The latest developments in China are introduced. The evaluation contents, the structure and index system of evaluation factors, the membership functions and weights of evaluation factor, evaluation model and reliability are stated in detail. The effective application of fuzzy evaluation in the prediction of coal face output is introduced emphatically. Fuzzy evaluationon geological conditions of coal seam is the basic work that ensures a mine run efficiently, safely and steadily . Keywords:Fuzzy evaluation; geological conditions; evaluation 1 INTRDUCTION To exploit the coal resource rationally means that the mining technical level and the relevant technical decisions are suitable for the characteristic and difference of coal geological conditions. If the evaluation is far below or above the actual geological conditions, it is unfavorable to make the most of the coal natural superiority and easy to make false technical decisions. So, it is very important to improve mining effects and economic benefits that the geological conditions are evaluated appropriately and the corresponding measures are taken. 2 CONTENTS OF FUZZY EVALUATION Based on the coal mining experience and rules summarized by widely investigation, the evaluation on geological conditions of coal seam should be taken by not only studying the influence of main factors to the selection of coal mining technology and mining effects, but also constructing a comprehensive supported by National Natural Science Foundation of China（NSFC） (50374065)，NSFC for extinguished scholars (50225414) evaluation model with multi-levels and multi-factors by the use of mining theory, fuzzy mathematics andAnalytic Hierarchy Process (called AHP for short), etc. In addition, the evaluation reliability should be considered in the application of evaluation results. So, the complete contents of fuzzy evaluation should include: (1) Investigating the experience and material of geological conditions, coal mining technology, technical effects, and safety state of face extraction in typical mining district. (2) Determining the structure of evaluation factors and the index system of geological factors, the membership functions and the weights of evaluation factors, and establishing the fuzzy evaluation model by summarizing the influence of geological factors to coal mining technology and using the methods of fuzzy mathematics, etc. K(3) Dividing the coal seam into many smaller blocks ij (i is coal seam number, j is block number.)Kijaccording to geological reports, and making pre-mining evaluation of the blocks to get the pre-mining evaluation value Pij. K(4) Making the second evaluation of typical blocks ij having been mined to get the evaluation valuePPij Pij according to the geological report and supplementary geological material after mining, is more suitable to practice. R = P(5) Analyzing the reliability of pre-mining evaluation, P( R is reliability index of the pre-mining evaluation K ), R 1. (6) Making evaluation on the blocks, based on the Pij and the Rij , the evaluation value of the blocks is:P0 = P Ri(7) Modifying the evaluation model or making a new evaluation according to its application and actual requirement. 3 STRUCTURE AND INDEX SYSTEM OF EVALUATION FACTORS The structure of evaluation factors reflects the connotation of evaluation. Its establishment should consider not only the general and specific difficult geological conditions, but also the principles of systematicness, feasibility and simplicity for the evaluation factors and indices obtained easily. Fuzzy evaluation on geological conditions of gently inclined or inclined coal seam in China consists of the evaluations for the general geological conditions and for the specific difficult geological conditions. The evaluation for the general geological conditions includes seven factors of geological structure, thickness of coal seam, stability of coal seam, pitch of coal seam, roof and floor of coal seam, hardness of coal seam and block dimension. The evaluation for the specific difficult geological conditions includes the other four factors of gas geology, hydrogeology, coal spontaneous combustion and the others besides the seven factors mentioned above. Furthermore, the geological structure contains three basic factors of fault, fold and magma. The stability of coal seam contains three basic factors of minability of coal seam, variability of coal seam and band coefficient. The roof and floor of coal seam contains four basic factors of immediate roof, main roof, false roof and immediate floor. The block dimension contains two basic factors of face length and advance length. So, there are fifteen basic factors altogether considering the thickness of coal seam, pitch of coal seam and hardness of coal seam. Quantitative indices should be selected rationally in order to evaluate the fifteen basic factors. 4 MEMBERSHIP FUNCTIONS OF EVALUA-TION FACTORS The membership function of evaluation factor is the quantitative description on fuzzy relationship between the change of a geological factor and the mining effect. It can be obtained by using technical summary, scientific research achievement, statistic analysis and specialist experience comprehensively, and adopting the statistic analysis method, undetermined coefficient method and heterogeneous fuzzy statistic method, etc. Figure 1(a), (b), (c) and (e) show the membership functions ma (a ), m m (m), ml (l)and m s (s)of coal seam pitch ( a ), thickness of coal seam (m), face length (l) and advance length (s). Membership functions of coal seam variance coefficient ( g ), minability of coal seam ( Km ), band (G ), immediate roof (o ), main roof ( N ), false roof (hv), immediate floor (Rc ) and magma (k) are m (r), m (K ), mG (G), m(s), mN (N ), m (h ), m (R ), mK (K ) , See fig.1. The membership functions mF(F) and mq (q) of fault (F) and fold (q) are where FN is the fault density, FL is the fault length coefficient, Fh is the fault drop height coefficient, q1 is the fold strength coefficient, q2 is the fold complexity coefficient.5 WEIGHTS OF EVALUATION FACTORS The essence of the weights of evaluation factors is the quantitative description on the relative importance of geological factors influencing the coal mining technology. To determine the weights of evaluation factors should take mining law as basis and take the mutual adaptability between geological condition and mining technology as main content, and should make full use of statistic data, research achievement and specialists experience. AHP is the method most in use at present. Based on the knowledge of specialist, this method is more suitable to solve the evaluation on geological conditions of concrete coal seam. Table 1 shows the weights of geological factors obtained by AHP. 6 FUZZY EVALUATION MODEL 6.1 Optimal Model For Fuzzy Evaluation The linear weighted comprehensive evaluation model is often used for fuzzy evaluation on geological conditions of coal seam. In recent years, the optimal model for fuzzy evaluation is presented to reduce the subjectivity of evaluation. Its main characteristic lies in using two -basic point method. That is to say, in the evaluation system with a number of blocks, there are an ideal point corresponding with good vector G (G=(g1, g2, ,gn) and an anti-ideal point corresponding with bad vector B (B=(b1, b2, ,bn). SupposeRR mihat the comprehensive evaluation values of i( i= (r11, r22, , r1m) is , and then compute the generalized distances D (Ri, G) and D (Ri, B). If taking the square sum of weighted distances of all samples as optimal criterion, the optimal solution of the comprehensive evaluation value is Figure 1. Membership functions of evaluation factors6.2 Comprehensive Evaluation Model For Special Difficult Conditions Based on above-mentioned fuzzy evaluation, a comprehensive evaluation model for special difficult geological conditions of coal seam is established to get the difficult coefficient D. The greater the value of D is the more difficult the geological mining conditions are. Because the influence of individual factor to whole evaluation should be embodied, continuous multiplication must be adopted when structuring the model. That is, D =1-B P, where B is the evaluation value of special geological conditions, P is the evaluation value of general geological conditions. Figure 2. Relationship between evaluation values and reliabilityFigure 2 shows the characteristic of reliability of pre-mining evaluation, based on the pre-mining and after -mining evaluation and calculation of evaluation reliability of 12 mining districts and 107 typical coal seam blocks. The greater the value of pre-mining evaluation is, the better the coal seam conditions are, and the higher the reliability of pre-mining evaluation is. On the contrary, the less the value of pre-mining evaluation is, the worse the coal seam conditions are, and the 8 PREDICTION OF COAL FACE OUTPUT Under the certain conditions of equipment, technique and management, there is a close relationship between coal face output and its geological conditions for a coal mine. Through the fuzzy evaluation on coal geological conditions and the statistic analysis on production-technique indices, the relationship between the coal face output and the fuzzy evaluation value can be fitted to establish a new model for the prediction of coal face output. There are many prediction models as linear equation, duality quadratic equation and exponential equation, etc. For example: a =C1 + C 2 P (fully-mechanized coal mining technology) a =D(C + CP + CP2) (fully-mechanized or conventionally-mechanized coal mining technology) a =D(C + CP + CP2 + CP3 ) (blasting coal mining technology)a =24.5(1.13 +1.24 ln P) (fully-mechanized coal mining technology with great power in Nantun Mine) a =(14.66ln M -6.77)(1.28 +1.4ln P) (fully-mechanized coal mining technology with sublevel caving in Dongtan Mine) where D is the difficult coefficient, C1, C2, C3, and C4 are statistic regression constants. REFERENCES 1I.B.Turksen 1991. Measurement of membership functions and their acquisition. Fuzzy sets and Systems. 40:36-40. 2North-Holland. R.Knosala & W.Pedrycz. 1992. Evaluation of de-sign alternative in mechanical engineering. Fuzzy sets and Systems. 47:24-28. 3J.S.Dyer & R.K.Sarin. 1979. Measurable Multi-attribute Value Function. Operations Research 煤层地质条件模糊综合评价在中国的应用张东升 张先尘 杨学峰江苏徐州中国矿业大学D摘要：地质条件煤层定量评价采用模糊方法和pointview采煤。根据评价结果，采矿技术决策，采矿规划与设计，生产管理可以有效地进行。本文介绍是中国的最新事态发展。评价的内容，结构和指标体系等评价因素，隶属函数和权重的评价因子，评价模型和可靠性是在细节。重点介绍有效应用模糊综合评价来预测采煤工作面产量。基本的工作式模糊综合评价的地质煤层条件，以确保煤矿高效，安全和稳步运行。关键词：模糊评价;地质条件评价1、简介合理利用煤炭资源意味着用采矿技术水平和相关技术决定适合不同特点和地质条件下的煤。如果评价是远低于或高于以上的实际地质情况，这对大多数煤炭自然优势是不利的并容易作出不实的技术决定。因此，地质条件评价和相应的适当采取措施对提高开采效果和经济效益是非常重要的。2、目录模糊评价基于广泛调查总结了的煤炭开采经验和规则，煤层地质条件评价不但应采取的学习选择煤炭开采技术和采矿业等主要影响因素而且而且还使用采矿理论建设多层次和多因素的综合评价模型，模糊数学和层次分析法（ AHP法要求短期）等。此外，评价的可靠性中应审议应用评价结果。因此，完整的模糊综合评价的内容应包括：（ 1 ）调查的经验和材料的地质条件，煤矿开采技术，技术的影响，以及国家的安全面临提取典型采区。（ 2 ）通过总结地质因素的影响，以煤炭开采技术和使用模糊数学方法等，确定评价的结构因素和指标体系的地质因素，隶属函数和权重的评价因素，建立模糊评价模型。（ 3 ）根据地质报告划分煤层成许多较小的块矩阵度Kij（i煤层号码， J是块号码。 ），并事先采矿评价块矩阵Kij并获得前采矿评估价值。（ 4 ）第二次评估典型块矩阵Kij已获得开采价值的评价矩阵Pij，根据地质报告和地质采矿补充材料矩阵Pij更适合应用。（ 5 ）采矿评价前的可靠性分析，矩阵矩阵矩阵Rij =Pij/Pij（矩阵R是采矿前评价可靠性指标矩阵Kij） ，矩阵R 1 。（ 6 ）依据Pij和Rij制作评价区块，评估价值的区块是：Pij = Pij Rij。（ 7 ）根据其申请和实际要求修改的评价模型或作出新的评价。3结构和指标体系的评价因素结构的评价因素反映内涵的评价。它的建立应考虑不仅是一般和特殊困难的地质条件，而且还有系统性，可行性和简单的评价因素和指标容易获得的原则。模糊综合评价在中国根据一般地质条件和地质条件的具体困难评估缓倾斜或倾斜煤层地质条件。在评价一般地质条件包括七个因素的地质构造，煤层厚度，稳定的煤层，音高煤层，顶底板的煤层，煤层硬度和拦截层面。在评价具体困难的地质条件，包括其他四个因素天然气地质学，水文地质学，煤炭自燃和其他7个因素，除了如上所述。此外，地质结构包含三个基本因素断层，褶皱和岩浆。稳定的煤层包含三个基本因素多层煤层，煤层变异与带系数。煤层顶底板的煤层包含四个基本要直接顶，老顶，伪顶和直接底。该区块的层面包含两个基本因素的工作面长度和推进长度。因此，有15个基本因素完全考虑煤的煤层厚度，煤层间距和煤层硬度。为了评估15基本因素应选择合理的定量指标。4隶属函数评价性因素隶属函数的评价因子是变化的地质因素和开采效果的定量描述的模糊关系。它可使用技术总结，科研成就，统计分析和全面专家经验，并通过统计分析方法，待定系数法和异构模糊统计方法，等获得。图1 a，b，c和e显示的隶属函数，煤层间距，m煤层厚度，l工作面长度，s推进长度，隶属函数煤层变异系数，minability煤层，直接顶，老顶