盾构机施工参数优化分析

发布时间：2018-05-18 05:01

本文选题：盾构法隧道 + 施工参数　；参考：《石家庄铁道大学》2015年硕士论文

【摘要】：随着我国隧道工程进入大规模建设阶段,作为先进的隧道施工技术,盾构法施工的应用也日益广泛。在不同的地质条件下,盾构机的千斤顶压力、推进速度、刀盘转速、注浆量等工作参数的匹配对施工效率的影响很大,盾构机运行状态的好坏决定了施工的质量和进度,是施工企业安全生产、提高效益、树立形象、服务社会的重要因素。基于上述原因,本文开展了对盾构机施工参数优化的深入而系统研究。首先,介绍了盾构法施工技术的研究背景和发展现状,对土压平衡盾构机的主要结构、土压平衡盾构技术和盾构法施工引起的地表沉降机理做了较为详细的研究,并结合工程实际,运用正交试验法,对盾构机施工参数进行了优化匹配和敏感度分析。然后将盾构机重要施工参数和当前沉降量作为输入量,下一阶段地表沉降量作为输出量,分别建立了基于BP神经网络和自适应神经模糊推理系统(ANFIS)的地表沉降预测模型,根据实时采集的盾构机施工参数和地表沉降数据,对预测模型进行了网络训练。训练误差达到期望后,对盾构施工引起的地表沉降进行了预测,预测结果与实际数据进行了比对和分析。实验结果表明,ANFIS在预测盾构施工引起的地表沉降方面具有很好的应用价值。神经网络和模糊推理相结合的方法在地表沉降预测方面具有广阔前景和发展优势。在ANFIS沉降预测模型的基础上,详细讨论了盾构机重要施工参数与地表沉降之间的关系。重点研究了盾构机重要施工参数分别以及共同对地表沉降的影响规律,并提出了盾构机施工参数合理的设定范围。国内对于盾构机施工参数间关系和匹配的规律研究相对滞后,对于施工参数的匹配和地表沉降的控制仍然停留在经验阶段。本课题对于典型的地质条件和线路条件下的盾构机施工参数与地表沉降的关系进行总结分析。根据盾构施工参数状态对地表沉降做出科学预测并通过盾构机施工参数之间的匹配优化,保证了开挖面的稳定,最大限度的减小地表沉降,对于盾构法施工具有较好的指导意义。
[Abstract]:As the advanced tunnel construction technology, shield method has been widely used in tunnel construction in China. Under different geological conditions, the matching of working parameters such as Jack pressure, propulsion speed, speed of cutter head and grouting quantity of shield machine has a great influence on the construction efficiency. The quality and progress of construction are determined by the running state of shield machine. Is the construction enterprise safe production, enhances the benefit, sets up the image, serves the society the important factor. Based on the above reasons, this paper carried out a thorough and systematic study on the optimization of shield machine construction parameters. Firstly, the research background and development status of shield construction technology are introduced, and the main structure of earth pressure balance shield machine, earth pressure balance shield technology and ground subsidence mechanism caused by shield construction are studied in detail. Combined with engineering practice, orthogonal test method is used to optimize matching and sensitivity analysis of shield machine construction parameters. Then taking the important construction parameters and current settlement of shield machine as input and the surface subsidence as output in the next stage, the prediction models of surface subsidence based on BP neural network and adaptive neural fuzzy inference system (ANFIS) are established, respectively. According to the real-time acquisition of shield machine construction parameters and surface subsidence data, the prediction model was trained by network. After the training error reaches the expectation, the ground subsidence caused by shield construction is forecasted, and the prediction results are compared and analyzed with the actual data. The experimental results show that ANFIS has a good application value in predicting the ground subsidence caused by shield tunneling. The combination of neural network and fuzzy reasoning has broad prospects and advantages in the prediction of surface subsidence. On the basis of ANFIS settlement prediction model, the relationship between the important construction parameters of shield machine and surface settlement is discussed in detail. The important construction parameters of shield machine and the law of common influence on surface subsidence are studied emphatically, and the reasonable setting range of construction parameters of shield machine is put forward. In China, the research on the relationship between the construction parameters and the matching law of shield machine is lagging behind, and the control of the construction parameters and the surface subsidence is still in the empirical stage. This paper summarizes and analyzes the relationship between the construction parameters of shield machine and surface subsidence under typical geological conditions and route conditions. According to the condition of shield construction parameters, the surface subsidence is predicted scientifically and optimized by matching the construction parameters of shield machine, which ensures the stability of excavating surface and minimizes the surface settlement. It has good guiding significance for shield construction.
【学位授予单位】：石家庄铁道大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U455.39

【参考文献】