论文总字数：18267字

摘 要

地铁，作为地下交通是一种时代的产物。它是在城市人口急剧增加、交通工具总量日益增长的今天，为了解决交通拥堵的现象、为了给人们带来快捷、便利、有序的乘车环境而开辟的又一道“捷径”。但是，地铁在给人们带来这诸多便利的同时也有不少问题需要我们去探究。在穿越既有线路、高大建筑物、深基坑等工程时，都会使原有的受力平衡被打破而发生一定的变形。如果这些因素不能得到及时的控制，都会导致严重的后果。因此，对地铁进行重点区域、多方面、多层次的监测以了解其整体状况就显得非常有必要。

目前，主要还是进行地铁隧道的局部监测。对于每个监测区域都有比较多的测量方法、测量仪器以及数据整理方法。本文则主要是针对隧道口断面上的监测点，利用测量机器人智能化、自动化的方法对数据进行获取，再将数据进行小波预处理、方差补偿自适应卡尔曼滤波的方法，进而对其进行形变量的预测。

关键字：自动化监测 变形监测 小波分析 卡尔曼滤波

Data Processing and Analysis of Subway Tunnel Automation Monitoring

ABSTRACT

The subway, as an underground transportation, is a product of the times. It is in the city population increased dramatically, the total transportation growing today, in order to solve the traffic congestion phenomenon, in order to bring convenient and orderly environment for passengers and has opened up a "shortcut". However, the subway brings many conveniences to the people, but there are also many problems that need us to explore. When crossing existing lines, tall buildings and deep foundation pit works, the original force balance is broken and a certain deformation occurs. If these factors can not be controlled in time, they will lead to serious consequences. Therefore, it is necessary to monitor the subway area in key, regional and multi levels so as to understand its overall situation.

At present, metro tunnels are mainly monitored locally. For each monitoring area, there are more measuring methods, measuring instruments and data processing methods. This paper is mainly aimed at the monitoring points of the tunnel section, the data acquisition method based on intelligent robot and automatic measurement, the method of data preprocessing, wavelet variance compensating adaptive Calman filtering, and then predict the deformation of the.

Keywords: automatic monitoring；deformation monitoring；wavelet analysis；Calman filtering

目 录

摘要............................................................ ............Ⅰ

ABSTRACT........................................................... ......Ⅱ

第一章 绪论..................................................................1

1.1 课题背景及意义...........................................................1

1.2 国内外研究现状...........................................................2

1.3 本文主要研究内容.........................................................2

1. 地铁隧道自动化监测方案的设计与实现...............................3

2.1 基准网与监测点的布设.....................................................5

2.1.1 监测点的布设.........................................................5

2.1.2 基准点的布设.........................................................6

2.2 测量机器人的测量方法.....................................................6

2.3 自动化监测的主要设备.....................................................6

2.4 本章小结.................................................................6

1. 数据处理方法.........................................................7

3.1 小波分析预处理的模型及其应用.............................................7

3.1.1 小波变换.............................................................8

3.1.2 常用的小波去噪方法...................................................9

3.1.3 小波变换阀值去噪函数的程序实现......................................11

3.2 卡尔曼滤波模型与分析....................................................12

3.2.1 卡尔曼滤波..........................................................13

3.2.2 模型的建立..........................................................14

3.2.3 精度评定............................................................15

3.3 本章小结................................................................16

第四章 苏州站变形监测实例分析............................................17

4.1 工程概况................................................................18

4.2 本章小结................................................................24

第五章 总结与展望..........................................................25

5.1 总结....................................................................25

5.2 展望....................................................................26

参考文献.................................................................... 27

致谢.........................................................................28

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