【作者】 李旋；

【导师】 陈永奇； 朱建军；

【作者基本信息】 中南大学 ， 大地测量学与测量工程， 2007， 硕士

【摘要】 GPS不仅具有自动化程度高、能够全天候观测、无需通视等优点,而且它还能获得大型工程结构物在风、温度等外力荷载作用下的高频振动位移和低频(似静态)的整体惯性偏移,因此GPS技术已成为工程结构健康监测一项重要手段。但GPS监测数据中不仅包含各种外力因素引起的变形,还含有多路径效应、残余对流层延迟等系统性误差影响。为此,本文利用小波分析及经验模式分解两种方法对GPS动态变形监测数据进行多尺度分析,以实现数据的滤波去噪、多路径效应等系统误差及变形特征提取等功能。具体内容有:1.GPS动态变形监测的数据特征分析:GPS动态变形监测数据中含有非线性、非平稳、复杂周期性变形信息以及噪声和系统误差等。2.小波多尺度和经验模式分解的基本理论:论述连续小波、离散小波变换、希尔伯特-黄变换中本征模态函数和经验模式分解的基本方法以及多尺度分析理论。3.基于小波分析的GPS动态变形监测多尺度分析方法,包括:预处理、时频域处理,并利用小波多尺度分析的方法实现振动数据的去噪、滤波和振动变形特征提取。4.基于经验模式分解的GPS动态变形监测多尺度分析方法的探讨。对模拟算例和实验数据加以分析,讨论基于经验模式分解的多尺度变形分析方法,并与小波多尺度分析方法进行了比较。5.建立基于小波和经验模式分解的组合多尺度变形分析方法。该方法克服了直接运用经验模式分解方法由大量噪声带来的不必要的干扰,减少了经营模式分解存在的边界效应和分解层数,提高了变形特征提取的准确性和时效性。更多还原

【Abstract】 Compared with traditional instruments, GPS has many advantages such as no weather condition and line-of-sight limited. The most important advantage is that GPS can measure both the high frequency and quasi-static displacement of large engineering structure under abnormal loading conditions such as during wind and temperature etc. So GPS has been increasingly used in structure health monitoring. However the GPS measurements include not only the real displacements of the structures, but also the quasi-system errors such as multipath and residual tropospheric delay. In order to filter the noise, mitigate the quasi-system errors and analyze the displacements, two multi-scale analysis methods, i.e. wavelet analysis and empirical mode decomposition are used in using GPS dynamic defomation monitoring. Following are the main contents of the thesis:1. Data characters analyse of dynamic deformation monitoring using GPS. It includes non-linearity, non-stationary, complex periodicity deformation, noises, system error and et al.2. The basic theories of muti-scale analysis, wavelet transform and empirical mode decomposition. The continue wavelet transform, discrete wavelet transform and empirical mode decomposition were discussed first. Then the basic theories of muti-scale analysis were discussed in detail.3. The multi-scale analysis method based on wavelet and its application in dynamic deformation monitoring. It includes denoising, data analysis in time-frequency domain, and extracting the properties of the dynamic deformations.4. The multi-scale analysis method based on empirical mode decomposition and its application in dynamic deformation monitoring. Simulated experiments and real GPS data were analyzed using empirical mode decomposition. The corresponding results were compared with the ones from wavelet method .5. A new multi-analysis method based on the combination of wavelet and empirical mode decomposition was developed. This method can overcome the disturb of noise using empirical mode decomposition, reduce the boundary effect and decomposition number, and improve the accuracy of the extracted properties of deformation.更多还原