發(fā)布時間：2018-06-10 06:17

  本文選題：礦井 + 熱害��； 參考：《西安科技大學》2013年碩士論文

【摘要】：隨著礦井開采深度的增加和采掘機械化程度的不斷提高，高溫熱害對礦井的安全生產(chǎn)和井下作業(yè)人員的身心健康造成了嚴重的威脅，導致礦井事故率上升、作業(yè)人員勞動率下降，煤礦的正常生產(chǎn)受到影響。因此，礦井降溫就變得越來越重要，而準確預測礦井風溫是合理設計通風空調(diào)系統(tǒng)的首要任務和重要基礎。 根據(jù)礦井風流熱濕交換原理，研究礦井各熱源對礦井風溫的影響因素，，在此基礎上，通過理論分析及合理簡化，確定影響井筒風溫、巷道風溫及工作面風溫的主要影響因素，為風溫預測模型輸入因子的確定提供了重要依據(jù)。 由于支持向量機具有良好的非線性系統(tǒng)的能力，可以有效的捕捉礦井風流溫度非線性變化規(guī)律和特性，并且支持向量機適用于小樣本數(shù)據(jù)的預測，解決礦井的預測樣本有限的問題。因此，應用支持向量機的方法，建立并優(yōu)化了基于支持向量機的礦井風溫預測模型。以礦井淋水井筒為例，將支持向量機應用于礦井淋水井筒風溫預測，通過理論分析和交叉試驗的方法，確定支持向量機類型、核函數(shù)及有關參數(shù)的選擇，預測結(jié)果表明，該支持向量機預測模型具有預測精度高、擬合效果好及計算速度快等優(yōu)點。 利用C語言編程，開發(fā)完成了基于支持向量機的礦井風溫預測軟件，用于礦井井筒、巷道、采掘工作面的風溫預測，該軟件同時具備建模和預測的功能，通過對軟件功能的界定表明，該軟件是具有可視化程度高、運算速度快、人機界面友好、實際操作方便的礦井風溫預測軟件。
[Abstract]:With the increase of mining depth and the increasing degree of mechanization of mining, the high temperature heat damage poses a serious threat to the safety of mine production and the physical and mental health of underground workers, which leads to the increase of mine accident rate. The normal production of coal mines has been affected by the decline of the labor rate of the workers. Therefore, mine cooling becomes more and more important, and accurate prediction of mine air temperature is the most important task and important foundation for rational design of ventilation and air conditioning system. This paper studies the influence factors of mine heat sources on mine air temperature. On the basis of this, through theoretical analysis and reasonable simplification, the main influencing factors of shaft air temperature, roadway air temperature and face air temperature are determined. It provides an important basis for determining the input factor of the wind temperature prediction model. Because the support vector machine has a good ability of nonlinear system, it can effectively capture the nonlinear variation law and characteristics of mine air temperature. Support vector machine (SVM) is suitable for prediction of small sample data to solve the problem of limited prediction samples in mines. Therefore, the prediction model of mine air temperature based on support vector machine is established and optimized by using support vector machine (SVM). The support vector machine (SVM) is applied to predict the air temperature of the well bore with mine flooding as an example. The selection of the type of support vector machine, kernel function and related parameters are determined by theoretical analysis and cross test. The prediction results show that the support vector machine can be used to predict the air temperature of the shaft. The prediction model of support vector machine has the advantages of high prediction precision, good fitting effect and fast calculation speed. By using C language programming, the prediction software of mine air temperature based on support vector machine is developed, which is used in mine shaft and roadway. The software has the function of modeling and forecasting simultaneously. The definition of the function of the software shows that the software has high visualization, fast operation speed and friendly man-machine interface. Practical operation of mine air temperature prediction software.
【學位授予單位】：西安科技大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TD727.2;TP181

【參考文獻】

相關期刊論文 前10條

1 王樹路;井下潮濕的危害不可忽視[J];煤炭工程師;1994年05期

2 周西華,單亞飛,王繼仁;井巷圍巖與風流的不穩(wěn)定換熱[J];遼寧工程技術大學學報(自然科學版);2002年03期

3 高建良;巷道斷面與風筒斷面形狀對局部通風工作面熱環(huán)境模擬結(jié)果的影響[J];焦作工學院學報(自然科學版);2004年01期

4 司千字;高溫礦井的熱環(huán)境處理[J];江蘇煤炭;1999年03期

5 鄭慧凡;白靜;李安桂;;BP神經(jīng)網(wǎng)絡在建筑物空調(diào)負荷預測中的應用評述[J];計算機應用與軟件;2007年06期

6 吳麗麗;羅新榮;;傾斜巷道風流熱環(huán)境數(shù)值模擬[J];礦業(yè)工程研究;2011年03期

7 楊德源;礦井風流熱交換[J];煤礦安全;2003年S1期

8 呂品;左金寶;倪小軍;;基于BP神經(jīng)網(wǎng)絡的礦井淋水井筒風溫預測[J];煤礦安全;2008年12期

9 何啟林,任克斌;深井建井期入風井筒風溫的預測[J];煤炭工程;2002年08期

10 周西華,王繼仁,盧國斌,單亞飛,梁棟;回采工作面溫度場分布規(guī)律的數(shù)值模擬[J];煤炭學報;2002年01期

本文編號：2002257