煤矿开采外文资料及中文翻译--综采工作面的安全性分析(编辑修改稿)内容摘要:

analyzing qualitatively the influence of main environment factors to coal mining safety, the relationship between mining accidents and environment factors such as temperature, humidity, illumination, yawp and gas is analyzed with the method of grey correlative analysis[5]. First, make the original data standardized. Secondly, calculate the 9 correlative coefficient. Finally, work out grey correlative degree. The calculation result indicates that grey correlative degree between mining accidents and gas is the largest. Therefore, gas is preponderant factor influencing mining accidents in Xinzhuang coal mine. 4. 2. Fuzzy clustering analysis of mining laces environment Clustering analysis is a method to classify objects according to some conditions or attributes of the objects. It is widely used in production and daily life. Environmental factors in mining faces are plex and uncertain. So how to classify is fuzzy. First, make the original data standardized. Secondly, establish fuzzy relationship. Finally, classify objects with the method of fuzzy clustering analysis[6]. All the mining faces in Xinzhuang coal mine are classified with this method. The result indicates that the environment of fully mechanized mining face is the best. The result also tells us how to improve the coal mining environment and where is the emphasis to strengthen management. This helps to decrease environmental influence to mining accidents and to improve mining safety. 4. 3. Countermeasures to improve underground environment After analyzing qualitatively and quantitatively the influence of underground environmental factors to mining accidents, we can distinguish the primary from the secondary. We can take some measures such as strengthening ventilation, installing air conditioner, eliminating noisy devices etc to improve underground environment so as to improve mining safety and ensure workers’ safety and sustained efficient production. 5. Grey entropy, synthetic evaluation on safety of mining faces 10 5. 1. Grey entropy Suppose a finite discrete sequence X={xi | i=1,2,……,n},grey entropy of sequence X is defined by l n xi xiH (X ) n1i (2) If xi=0,let xi ln xi=0 5. 2. Balanced degree Grey entropy is the measure to balance degree of elements in discrete sequence X in terms of grey entropy increase theorem[7]. The greater grey entropy is the more balanced the discrete sequence is. For a discrete sequence with n elements the maximum entropy is a constant ln n which is only relevant with the number, of elements in sequence when all elements are equal. Thus, balanced degree of sequence can be defined by B=H(X)/Hm (3) Where Hm is the maximum grey entropy. 5. 3. Grey correlative degree Grey correlative degree is the measure to adjacent degree between the reference sequence and relative sequence. It can be calculated by correlative coefficients[8]. The correlative coefficient can be calculated by the following equation. ikkkiikkikkkiikkkii vvm a xm a xvvvm a xm a xvvm i nm i nkL  v)( (4) Where ρ is distinguished coefficient, it is in the range from 0 to 11 1. Usually it is 0. 5. Grey correlative degree can be expressed as.  n1kioi kLn1r )( (5) Where oir is grey correlative degree between the reference sequence and the thi relative sequence. 5. 4. Model of multilevel grey entropy synthetic evaluation If the evaluation indices lie in different levels. We should apply the model of multilevel grey entropy synthetic evaluation . Multilevel evaluation model is similar to single level evaluation model . The secondorder evaluation results from the firstorder evaluation matrix. The evaluation result matrix can be obtained by weight vector and the evaluation matrix in view of the significance difference of indices in the first level. It can be expressed by W=A2W (6) where 2W is the balanced adjacent degree matrix. 5. 5. Synthetic evaluation on mining faces in Xinzhuang coal mine Table 1 shows evaluation indices and original data of mining faces in Xinzhuang coal mine. At first, the secondorder synthetic evaluations are carried out respectively. The process of evaluation is omitted. The evaluation results are shown in Table 2. Table 1 Or。
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