基于傅里叶变换轮廓术的地表沉降监测技术研究

发布时间：2018-01-20 03:14

本文关键词： 地表沉降摄像机标定条纹投影离散傅里叶变换图像匹配　出处：《西安科技大学》2017年硕士论文　论文类型：学位论文

【摘要】：地表沉降是当今世界各国城市化进程中普遍存在和不容忽视的环境地质问题,这种连续的、渐进的、累加式地质灾害主要由经济高速发展过程中不断加大地下资源开发引起,由此引发的房屋开裂、建筑走形、水涝频发、局部坍塌等问题严重制约了区域经济可持续发展、威胁到人类生命及财产安全。传统的地表沉降监测方法多采用水准测量、GPS等简易人为监测设备,这些设备在控制过程及输出效果上,存在着诸多不足之处。因此,对于地表沉降的研究就显得十分必要且刻不容缓。针对传统监测方法中存在观测周期长、效率低下、实时性较差等问题,本文以彩色条纹投影为研究对象,使用摄像机标定配合傅里叶变换轮廓技术,恢复被测地表的三维轮廓信息,提出了一种基于差影法和NCC相融合的方法来进行地表沉降监测,并进行了可行性验证。具体工作如下:首先,为了进行实验仿真及后续研究内容的正常推进,搭建了一个基于条纹投影轮廓术的实验测量系统,它的功能包含了条纹投影、变形条纹图的采集,并完成了摄像机标定实验,获得摄像机的内部和外部参数;其次采集了被测模拟地表运动数据信息,综合对比分析了常用光学三维测量方法优劣势以及与本论文研究内容的契合度,选择了基于三频条纹投影的傅里叶变换轮廓术作为地表沉降监测的理论指导模型,重点讨论了背景消减、经验模式分解、颜色解耦、变精度相位去包裹等相关技术;在此基础上,模拟完成了对于地表运动信息的监测实验,实验结果表明了正弦条纹投影方法在地表沉降监测方面的可行性;最后为了判定被测地表的变形程度,本文在已有研究的基础上,提出了一种基于差影法和NCC相融合的方法来进行图像匹配,并与传统NCC算法进行了对比,仿真结果表明:该融合算法在处理时间方面比NCC算法减少至2s,实时性较好。地表沉降监测实验表明:基于条纹投影的傅里叶变换轮廓技术,实现了对地表变形情况的实时监测,提高了整个监测过程的处理时间,使该系统具有更强的鲁棒性,并且系统的测量精度达到毫米级别,在地表沉降监测方面具有一定的社会价值。
[Abstract]:Surface subsidence is a continuous and progressive environmental geological problem in the process of urbanization all over the world. The accumulative geological hazards are mainly caused by the increasing development of underground resources in the process of rapid economic development, resulting in building cracking, building shape, frequent waterlogging. Local collapse seriously restricts the sustainable development of regional economy and threatens the safety of human life and property. Traditional surface subsidence monitoring methods often use simple artificial monitoring equipment such as leveling and GPS. There are many deficiencies in the control process and output effect of these equipments. Therefore, the study of surface subsidence is very necessary and urgent. There is a long observation period in the traditional monitoring methods. In this paper, the color fringe projection is taken as the research object, the camera calibration and Fourier transform contour technology are used to restore the 3D contour information of the measured surface. A method based on subtraction and NCC fusion is proposed to monitor surface subsidence, and the feasibility is verified. The detailed work is as follows: first. In order to carry out the experiment simulation and the normal advance of the following research content, an experimental measurement system based on fringe projection profilometry is built. Its function includes fringe projection and the acquisition of deformation fringe image. The camera calibration experiment is completed and the internal and external parameters of the camera are obtained. Secondly, the information of simulated ground motion data is collected, and the advantages and disadvantages of the commonly used optical 3D measurement methods are compared and analyzed, as well as the degree of agreement with the content of this paper. Fourier transform profilometry based on triple-frequency fringe projection is selected as the theoretical guidance model for surface subsidence monitoring. Background subtraction empirical mode decomposition and color decoupling are discussed in detail. Variable precision phase unwrapping and other related technologies; On this basis, the experiment of monitoring the ground motion information is completed, and the experimental results show the feasibility of the sinusoidal fringe projection method in the monitoring of surface subsidence. Finally, in order to determine the deformation degree of the measured surface, this paper proposes a method of image matching based on subtraction and NCC fusion. Compared with the traditional NCC algorithm, the simulation results show that the processing time of the fusion algorithm is less than that of the NCC algorithm to 2 s. The experiment of surface subsidence monitoring shows that the Fourier transform contour technology based on fringe projection can realize the real-time monitoring of surface deformation and improve the processing time of the whole monitoring process. It makes the system more robust, and the measuring accuracy of the system reaches millimeter level, which has certain social value in the monitoring of surface subsidence.
【学位授予单位】：西安科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P642.26

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