盾构机密封舱多点土压平衡优化控制策略

发布时间：2018-03-19 03:12

本文选题：盾构机　切入点：多点土压平衡　出处：《大连理工大学》2015年硕士论文　论文类型：学位论文

【摘要】：土压平衡盾构机是一种地下隧道施工中的专用工程机械,是目前最为先进的新型盾构,被广泛应用于地铁隧道、公路隧道、水利工程等地下工程建设。盾构施工过程中,掘进面压力失衡是导致地表塌陷或隆起等安全事故的主要原因,保持掘进面与盾构机密封舱之间的土压平衡是安全、高效施工的关键。地质条件的随机多样性与多场耦合作用使得掘进面的物理和力学行为极为复杂、难以预测,因而目前实际施工中的土压平衡控制仍主要依靠人工经验来进行。因此,实现盾构机密封舱土压平衡的自动控制是盾构技术研究中的重要课题。本文在对盾构掘进过程进行机理分析的基础上,结合先进控制理论与优化算法,对盾构机密封舱多点土压平衡优化控制策略进行了研究,主要工作如下：(1)对盾构技术的研究背景、起源、国内外发展情况等进行了概述,阐明了本文的研究意义。简述土压平衡盾构机的构造以及工作原理,并对盾构掘进过程中的开挖面稳定机理进行了说明。(2)通过对盾构掘进过程进行机理分析,综合考虑了盾构机总推力、推进速度、螺旋输送机转速耦合作用对掘进面稳定性的影响,以密封舱隔板上带有四个土压传感器的土压平衡盾构机为例,基于自适应神经模糊推理系统,提出了以总推力、推进速度、螺旋输送机转速以及当前时刻土压值为输入变量,以下一时刻的土压值为输出变量的多点土压预测模型。采用现场施工数据对模型进行了仿真验证,结果表明,该模型能够较为精确的对密封舱内的土体压力进行预测。(3)以各压力点土压预测值与对应的土压设定值之间的绝对误差之和最小为优化目标,提出了采用蚁群算法求解最优螺旋输送机转速的盾构机密封舱多点土压平衡优化控制方法,并分别结合密封舱隔板上带有四个土压传感器和五个土压传感器的两种土压平衡盾构机现场施工数据对优化控制策略进行仿真验证,结果表明,优化后土压与设定值之间的均方根误差比优化前减小了一个数量级,取得了满意的控制效果,验证了该方法的有效性。
[Abstract]:Earth pressure balance shield machine is a kind of special construction machinery in underground tunnel construction. It is the most advanced new shield machine and is widely used in underground construction of subway tunnel, highway tunnel, water conservancy engineering and so on. The unbalance of tunneling surface pressure is the main cause of safety accidents, such as surface collapse or uplift, and it is safe to maintain the earth pressure balance between the tunneling surface and the shield machine seal cabin. The random diversity of geological conditions and the coupling of multiple fields make the physical and mechanical behavior of the tunneling surface extremely complicated and difficult to predict. Therefore, the control of soil pressure balance in actual construction still depends mainly on manual experience. The realization of automatic control of earth pressure balance in shield machine seal cabin is an important subject in the research of shield tunneling technology. Based on the mechanism analysis of shield tunneling process, this paper combines advanced control theory and optimization algorithm. The optimal control strategy of multi-point earth pressure balance of shield machine seal cabin is studied. The main work is as follows: 1) the research background, origin and development of shield machine technology are summarized. The research significance of this paper is expounded. The structure and working principle of earth pressure balance shield machine are briefly described, and the stability mechanism of excavating surface during shield tunneling is explained. (2) the mechanism analysis of shield tunneling process is carried out. The influence of the coupling effect of the total thrust, propulsion speed and rotating speed of the shield machine on the stability of the tunneling surface is considered synthetically. The earth pressure balance shield machine with four earth pressure sensors on the seal compartment is taken as an example. Based on the adaptive neural fuzzy inference system, the total thrust, propulsion speed, rotating speed of the screw conveyor and the earth pressure at the present time are taken as input variables. The prediction model of soil pressure at the following moment is a multi-point soil pressure prediction model with output variables. The simulation results show that the model is verified by field construction data. The model can accurately predict the soil pressure in the sealed tank. The optimal objective is to minimize the absolute error between the predicted value of soil pressure at each pressure point and the corresponding set value of soil pressure. An optimal control method for multi-point earth pressure balance of seal cabin of shield machine based on ant colony algorithm is proposed to solve the optimal speed of spiral conveyor. Two kinds of earth pressure balance shield machine with four earth pressure sensors and five earth pressure sensors are used to simulate the optimal control strategy. The root-mean-square error between the optimized soil pressure and the set value is reduced by an order of magnitude compared with that before optimization. The satisfactory control effect is obtained and the effectiveness of the method is verified.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U455.39

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