【作者】 王侠；

【导师】 程乃伟；

【作者基本信息】 沈阳航空工业学院 ， 安全技术及工程， 2010， 硕士

【摘要】 随着现代大型公共建筑的不断增多,火灾隐患与火灾事故层出不穷,给建筑的消防系统带来了严峻的考验。提高安全疏散的效率以减少火灾时的人员伤亡,是当今消防疏散设计的新课题。基于现代建筑的大型化、复杂化本文提出了一种新的智能化疏散方法——动态疏散。它有别于传统的借助于报警装置以及独立的、固定的疏散指示灯来引导人们逃生的静态疏散模式,而是通过搜集火灾现场的一系列动态信息,并对这些信息进行分析、计算,从而得出各个节点的风险大小,找出风险最小且疏散距离最短的疏散路径,即为最优疏散路径。因此疏散路径是随着环境的改变而改变的。本文研究的重点是应用一种计算最优路径的有效方法,从而可以及时的更新最优路径,大大提高疏散效率。本文综合分析了火灾现场危险因素及人员行为特征,并深入研究了Dijkstra算法、模拟退火算法、遗传算法、蚁群算法等几种经典的路径诱导算法。由于蚁群算法具有发现较优解的能力,不易陷入局部最优,而且在所有问题上的性能都优于其他算法。因此本文最终确定蚁群算法作为动态疏散路径优化的方法,并通过实例证明,蚁群算法能够实时跟踪火场环境变化并及时输出新的全局最优路径。更多还原

【Abstract】 With the continuous increasing of modern large-scale public buildings, fire risks and fire incident frequently happen, which bring a big challenge to the fire control system of constructions. Nowadays the fire evacuation design needs to focus on safety evacuation efficiency’s improvement and fire casualties’reduction.Based on the large-scale and complex of modern architecture, a new intelligent evacuation method which was called dynamic evacuation has been suggested. It is different from the traditional static evacuation depending on alarm devices and independent and fixed evacuation lights to guide people escaping. Dynamic evacuation is just that collect a series of dynamic information at the fire scene, and then get the degree of risk of all nodes through doing the information analysis and calculation work, and find an optimal evacuation being the shortest distance of minimum risk. So evacuation path changes with the environment changing.This paper focuses on the application of a method calculating an optimal path effectively, which can replace the optimal path in time and greatly enhanced the evacuation efficiency. This paper analyzes the risk factors of fire scene and the behavior characteristics of attendee, and deeply does the study of the classic route guidance algorithms like dijkstra algorithm, simulated annealing algorithm, genetic algorithm, ant colony algorithm and so on. As the ant colony algorithm can find better solutions and not focus local optimum, its performance is better than others in all matters. Therefore, this article determines the ant colony algorithm to be dynamic path evacuation optimization method ultimately. And examples prove that the method can track environmental changes in real time and output a new global optimal path in time更多还原