【摘要】：礦井通風(fēng)網(wǎng)絡(luò)解算的理論和算法研究早在70年代就已經(jīng)成熟,但時(shí)至今日通風(fēng)網(wǎng)絡(luò)解算仍然沒有在礦井生產(chǎn)實(shí)際應(yīng)用中得到廣泛的應(yīng)用.通風(fēng)網(wǎng)絡(luò)解算應(yīng)用的3大瓶頸問題之一的通風(fēng)阻力系數(shù)“測(cè)不準(zhǔn),總在變”的問題,時(shí)至今日該問題尚未解決,阻礙了通風(fēng)網(wǎng)絡(luò)解算在實(shí)際中的應(yīng)用.巷道風(fēng)阻可通過經(jīng)驗(yàn)公式計(jì)算和通風(fēng)阻力測(cè)試獲取.風(fēng)阻經(jīng)驗(yàn)公式通常只是一些特殊情況的近似歸納,一些常量參數(shù)取值更多的依賴人為經(jīng)驗(yàn),存在較大的主觀性誤差；而現(xiàn)場(chǎng)測(cè)試工作量非常大且費(fèi)時(shí)、費(fèi)力.無論是經(jīng)驗(yàn)公式還是現(xiàn)場(chǎng)測(cè)試,得到的風(fēng)阻數(shù)據(jù)都存在誤差,使得仿真計(jì)算的結(jié)果與實(shí)際的通風(fēng)系統(tǒng)不匹配.如何通過少量代表性巷道風(fēng)量、節(jié)點(diǎn)壓力等有限的實(shí)測(cè)數(shù)據(jù),反演礦井通風(fēng)系統(tǒng)阻力系數(shù),這是一項(xiàng)值得研究的課題.目前國(guó)內(nèi)外關(guān)于通風(fēng)阻力系數(shù)反演研究較少,基于國(guó)家自然基金資助項(xiàng)目(60772159)《基于仿真技術(shù)的礦井通風(fēng)系統(tǒng)智能診斷系統(tǒng)研究》,開展本文研究工作.從流體網(wǎng)絡(luò)三大基本定律出發(fā),建立通風(fēng)阻力系數(shù)反演的矩陣方程組形式.無論是多測(cè)點(diǎn)一次觀測(cè)還是少測(cè)點(diǎn)多次觀測(cè)條件下,利用有限的巷道風(fēng)量和節(jié)點(diǎn)壓力觀測(cè)數(shù)據(jù)來反演通風(fēng)系統(tǒng)中的各條巷道風(fēng)阻,由于方程數(shù)小于未知變量個(gè)數(shù),反演問題始終存在多解的情況,通風(fēng)阻力系數(shù)反演問題是不適定的.基于最小二乘原理建立了通風(fēng)阻力系數(shù)反演的數(shù)學(xué)模型,以實(shí)測(cè)壓力與與計(jì)算壓力的偏差以及實(shí)測(cè)風(fēng)量與計(jì)算風(fēng)量的偏差為目標(biāo)函數(shù),綜合考慮了壓力、風(fēng)量以及通風(fēng)阻力系數(shù)范圍約束,通過該模型的建立將通風(fēng)阻力系數(shù)反演問題轉(zhuǎn)化非線性優(yōu)化問題.采用遺傳算法和粒子群算法來求解基于最小二乘原理的通風(fēng)阻力系數(shù)反演的優(yōu)化問題.針對(duì)通風(fēng)阻力系數(shù)反演問題,對(duì)遺傳算法和粒子群算進(jìn)行了改進(jìn),增強(qiáng)算法的全局搜索和局部搜索能力.上述研究基礎(chǔ)上,可以依據(jù)觀測(cè)點(diǎn)相對(duì)靈敏度選擇合適的觀測(cè)數(shù)據(jù)進(jìn)行通風(fēng)阻力系數(shù)反演.結(jié)合通風(fēng)系統(tǒng)靈敏度理論和聚類分析理論,提出了一種基于反映通風(fēng)系統(tǒng)阻力系數(shù)變化的巷道風(fēng)量測(cè)點(diǎn)和節(jié)點(diǎn)壓力測(cè)點(diǎn)布置方法,對(duì)通風(fēng)系統(tǒng)中可以觀測(cè)的巷道、節(jié)點(diǎn)進(jìn)行分類,尋找少量代表性強(qiáng)的分支風(fēng)量測(cè)點(diǎn)和節(jié)點(diǎn)壓力測(cè)量,最大可能的反映通風(fēng)系統(tǒng)的實(shí)際運(yùn)行狀態(tài),減少測(cè)試工作量.最后通過實(shí)例描述了基于粒子群算法的寺河礦二號(hào)井通風(fēng)阻力系數(shù)反演過程,驗(yàn)證了反演方法的可行性,為進(jìn)一步的研究通風(fēng)阻力系數(shù)反演問題以及實(shí)際工程應(yīng)用奠定了基礎(chǔ),具有重要的指導(dǎo)意義.
[Abstract]:The theory and algorithm of mine ventilation network calculation have been mature since 1970s, but the ventilation network calculation has not been widely used in mine production. One of the three bottleneck problems in the application of ventilation network calculation is the problem of "uncertainty, total change" of ventilation resistance coefficient. Up to now, this problem has not been solved, which hinders the application of ventilation network calculation in practice. Roadway wind resistance can be calculated by empirical formula and ventilation resistance test. The empirical formula of wind resistance is usually an approximate induction of some special cases, and some constant parameters are more dependent on human experience, and there is a large subjective error, while the field test work is very heavy, time-consuming and laborious. No matter the empirical formula or the field test, there are errors in the wind resistance data, which makes the simulation results do not match the actual ventilation system. How to retrieve the resistance coefficient of mine ventilation system through a small amount of representative tunnel air volume, node pressure and other limited measured data is a subject worth studying. At present, there are few researches on the inversion of ventilation resistance coefficient at home and abroad. Based on the project funded by the National Natural Fund (60772159) < Research on Intelligent diagnosis system of Mine ventilation system based on Simulation Technology ", the research work is carried out in this paper. Based on the three basic laws of fluid network, the matrix equations of ventilation resistance coefficient inversion are established. Under the condition of multiple observation points or multiple observation points, the wind resistance of each tunnel in ventilation system can be retrieved by using the limited observation data of tunnel air volume and node pressure, because the number of equations is less than the number of unknown variables. The inversion problem always has multiple solutions, and the ventilation resistance coefficient inversion problem is ill-posed. Based on the least square principle, a mathematical model of ventilation resistance coefficient inversion is established. The deviation between measured and calculated pressure and between measured and calculated air volume is taken as the objective function, and the pressure is considered synthetically. Through the establishment of the model, the inversion problem of ventilation resistance coefficient is transformed into a nonlinear optimization problem. Genetic algorithm and particle swarm optimization algorithm are used to solve the optimization problem of ventilation resistance coefficient inversion based on least square principle. For the problem of ventilation resistance coefficient inversion, genetic algorithm and particle swarm optimization are improved to enhance the global and local search ability of the algorithm. Based on the above research, the ventilation resistance coefficient can be retrieved according to the relative sensitivity of observation points. Based on the sensitivity theory of ventilation system and the cluster analysis theory, a method of layout of air flow measurement points and nodal pressure measuring points of roadway based on the change of resistance coefficient of ventilation system is proposed. The nodes are classified to find a small number of representative branch air flow measurement points and node pressure measurement to reflect the actual operating state of the ventilation system and reduce the test workload. Finally, the inversion process of ventilation resistance coefficient of Sihe No. 2 well based on particle swarm optimization is described, which verifies the feasibility of the inversion method, and lays a foundation for further research on the inversion of ventilation resistance coefficient and its practical engineering application. It has important guiding significance.
【學(xué)位授予單位】：遼寧工程技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TD724

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