【作者】 梁双华；

【导师】 汪云甲；

【作者基本信息】 中国矿业大学 ， 地图制图学与地理信息工程， 2013， 博士

【摘要】 对井下瓦斯及时、有效地监控，传感器布置方式至关重要。现行煤矿安全规程及相关规范采用的一些布置参数多来源于现场实践经验，其主要关注致灾因素间耦合模式相对固定的高风险点即瓦斯安全关注点，较少顾及瓦斯监测点点间距、点密度和空间分布等情况，导致瓦斯监测存在预报预警风险缺陷。因此，研究满足预警要求且经济可行的瓦斯传感器无盲区布置的优化选址方法对提高监测系统性能、预防重特大瓦斯事故的发生具有重要价值。论文以矿井复杂通风巷道的瓦斯监测点优化选址问题为研究对象，在对相关文献回顾与总结的基础上，采用信息熵、层次分析法、禁忌-蚁群算法、混合PACA算法及空间数据处理技术，对矿井通风巷道瓦斯传感器优化选址模型建模、模型的高效求解算法和瓦斯传感器选址决策支持系统的构建等问题进行创新性研究，以期为矿井瓦斯传感器的优化布置提供一些新方法和新思路。（1）为实现高风险区域的瓦斯灾害防备，论文基于矿井通风巷道瓦斯涌出与运移表现特性，借鉴安全评价方法和不确定性理论，确定了瓦斯积聚影响因素的评价指标体系，建立了基于信息熵的瓦斯积聚危险性评价模型，并以山西北茹矿为例，验证本文所建立的瓦斯积聚危险性评价方法，得出的积聚危险规律现场应用效果良好。（2）论文将设施选址理论引入瓦斯传感器优化布置中，在对瓦斯传感器设施选址特征进行深入剖析的基础上，应用宏观模型和微观模型相结合的优化思想，提出了兼顾监测覆盖范围和瓦斯安全关注点的瓦斯传感器布置方式，借助图论理论、设施覆盖选址理论和线性规划方法建立了四类基于不同选址目标的瓦斯传感器选址模型，并对上述模型进行了拓展，提出了分区分级瓦斯传感器选址模型，对模型的应用和处理方法进行了实例验证。（3）针对本文提出的瓦斯传感器选址模型采用精确算法难以求解的问题，设计了启发式的基于列减少算法、禁忌搜索和蚁群算法的三阶段混合蚁群算法，详细讨论了混合算法的组合框架、策略设计、约束条件的处理和求解步骤等内容，并运用算例求解对比，验证了混合蚁群算法求解瓦斯传感器选址模型的可行性、先进性和有效性。（4）设计开发了基于GIS的瓦斯传感器优化选址决策支持系统。运用Geodatabase几何网络模型对矿井通风网络进行了建模，以此为基础实现了关键功能模块的研发，有效地降低了系统的开发难度，应用于实际矿井，取得了良好的效果。更多还原

【Abstract】 To timely and effectively monitor coal gas, methane sensor arrangements modesare of crucial importance. Currently, arrange parameters proposed by coal mine safetyregulations and correlative specifications mostly originate from experience and arechiefly concerned with high risk points, namely, methane safety security concerns,where disaster factors are easy to couple, however, the distance between two points,points density and spatial distribution etc, are always ignored, Which led to the risk inmethane forewarning. Therefore, study the reasonable, economic and meeting warningneeds methane sensor placement are of significant value in enhancing monitoringsystem performance and preventing the occurrence of major gas accidents.The topic of this research is the optimal placement of coal gas monitoring points incomplexity ventilation roadways. Based on the relevant literature reviewed andsummaries, the following subjects, which are the model modeling of methane sensoroptimal placement in complexity ventilation roadway, an efficient algorithmconstruction for solving models and development of decision supporting system formethane sensor placement are innovatively studied, by the techniques of Shannonentropy, analytic hierarchy process model, facilities covering location models, TabuSearch Algorithm (TS), Ant Colony Algorithm (ACA), hybrid Pareto Ant ColonyAlgorithm (HPACA) and spatial data processing, in order to provide some new methodsand ideas about mine methane sensor optimal placement.(1) The assessment index system and the risk evaluation model which based oninformation entropy of gas accumulation in a mine ventilation system are established bythe techniques of safety evaluation method in the field of system engineering anduncertainty theory, on the basis of characteristics of airflow, gas emission and migrationin the airway. Taking Shanxi Beiru Coal Mine for an example, the feasibility of theinformation entropy risk assessment approach is confirmed, and the law of the gasaccumulation is proved effective.(2) It is the first time to introduce the facility location theory into the research onmethane sensor optimal placement. A methane sensor layout mode of comprehensivelyconsidering the sensor monitoring coverage and the methane safety impact points areproposed based on the probing into the facility location characteristics of methanesensor and the thinking of combination of the macroscopic model and the microscopicone. Four optimization models of methane sensor placement in different location targetswere established by means of graph theory, set covering theory and linear programming method. Partition hierarchical Location model of methane sensor was proposedbased on the typical models. The concrete example validations of models applicationand treatment methods are given in the thesis.(3) In view of the difficulty of the exact algorithm in solving the models ofmethane sensor placement, a three-stage Hybrid Ant Colony optimization Algorithmmethod combined with column reduce algorithm, Tabu Search (TS) and ant colonyoptimization algorithm (ACA) was designed. The combination frame, strategy design,the processing of constrained conditions and solution procedure are discussed in detail.Application of actual calculation example verified the feasibility, effectiveness andadvancement of the model solving algorithm.(4) The decision supporting system is designed and developed for methane sensorplacement based on GIS. Key function modules are developed based on the mineventilation network which established by the GIS geometric network model, in this waythe development difficulty of the system was reduced, good result with the applicationin a real mine is hence forth obtained.更多还原