【作者】 刘建国；

【导师】 杨建华；

【作者基本信息】 长安大学 ， 大地测量学与测量工程， 2010， 硕士

【摘要】 随着我国经济持续稳定的高速发展,高速铁路的修建越来越多。作为关乎国民经济发展的重要基础设施,中国高度重视铁路建设,投资大幅增加。高速铁路要为列车的高速行驶提供一个高平顺性和高稳定性的轨下基础,而桩基作为轨道结构的基础,必须在运营条件下将线路轨道的设计参数保持在要求的标准范围之内,这无疑就对高速铁路的沉降稳定提出了很高的要求。因此,桩基的沉降稳定性以及沉降预测成了高速铁路路基设计和施工的关键。本文以京沪高铁——昆山段为背景,对桥梁进行定期沉降观测,并对变形数据进行分析处理,并结合当地的地质特征及地质条件,从京沪高铁沉降监测网的建立、观测内容、观测精度、观测频度等方面做比较系统的论述,特别对桩基、桥涵、隧道以及过渡段的沉降观测作了深入研究。研究了卡尔曼滤波模型和动态神经网络模型在桥梁形变预测中的应用,并在二者的基础上采用了一种基于卡尔曼滤波算法的BP神经网络模型,这种模型能够综合二者的优点,预测精度有了很大的提高。本文中将这种模型应用于桥梁桩基的沉降预测,并取得了较好的效果,为桥梁桩基的沉降预测提供了新的思路。更多还原

【Abstract】 Continues the stable high speed development along with our country economy, the high-speed railroad construction are more and more many.As concerns the national economy development the important infrastructure, China takes the railroad construction highly, the investment large increase. The high-speed railroad must provide a hing smooth compliance and under the high stable axle for the train high speed travel the foundation, but the pile foundation took the orbital structure the foundation, must maintain under the operation condition the line track design variable in the request standard scope, this without doubt on stably set the very high request to the high-speed railroad subsidence.Therefore, the pile foundation subsidence stability as well as the subsidence forecast the high-speed railroad grade location and the construction key.This article by Beijing to Shanghai high-valence iron--take Beijing to Shanghai high-valence iron as an example, Periodically to pile settlement observation, and unifies local the geological feature and the geological condition, from Beijing to Shanghai high-valence iron subsidence aspects and so on monitoring network establishment, observation content, observation precision, observation frequency makes the quite systematic elaboration, specially to the pile foundation, the arch of bridge, the tunnel as well as the change-over portion settlement observation has done the thorough research.Has studied the Kalman filtering model and the dynamic neural network model in bridge deformation forecast application, and used in the two foundation one kind based on the Kalman filtering algorithm BP neural network model, this kind of model can synthesize the two the merit, forecast the precision had the very big enhancement. This will be the model is applied to predict the settlement of pile foundation, bridge and achieved good effect, the settlement of pile foundation for the bridge for new ideas.更多还原