基于wMPS空间测量场的动态测量定位方法与技术研究

发布时间：2018-03-31 04:22

本文选题：大尺寸动态测量技术　切入点：动态测量性能　出处：《天津大学》2016年博士论文

【摘要】：wMPS(workspace Measuring and Positioning System)是一种基于光电扫描的新型网络式大尺寸三维坐标测量系统,具有量程覆盖大、自动化程度高、抗干扰能力强、可实现多任务同步测量等优势。目前对wMPS的静态测量性能及精度有了较为系统和全面的研究,然而,对其动态测量性能和动态测量误差分析的相关研究不足。本文在优化全局组网定向方法的前提下,研究了系统动态测量误差模型,以此为基础通过多发射站间同步误差补偿和采用卡尔曼滤波模型来减小系统动态测量误差,并进行了实验验证,最终提升了wMPS动态测量性能。主要研究内容如下:1.总结了在大型装备制造业中对于先进大尺寸动态测量技术的迫切需求,分析现有的多种测量方法的优势和局限,阐述wMPS在解决现场条件下大尺寸动态测量问题中的潜在能力,同时分析其动态测量特性,重点分析了相位误差和同步误差对动态测量的影响,为提高动态测量性能提供理论依据。2.构建高精度的大尺寸测量场是实现wMPS动态性能的前提,研究了基于控制场和基于相对约束控制联合平差的两种组网定向方法,阐述了定向模型及迭代初值获取的方法,并分析了两种方法的优缺点,最后通过实验对两种方法的可行性和精度进行了验证,为wMPS动态测量提供了高精度网络结构基础。3.针对多发射站间同步误差补偿问题,通过在信号处理器内部搭建基于Microblaze的SOPC嵌入式处理系统,实现多通道信号在同一时间基准下的触发、采集,将每个发射站的接收信息时间标记。以此为前提引入拉格朗日插值法实现多发射站间测量信息同步,补偿了多发射站间同步误差,并通过相关实验进行验证,提高了动态测量精度。4.结合目标的运动特性,引入卡尔曼滤波算法进一步减小动态测量误差,构建了基于线性卡尔曼滤波和扩展卡尔曼滤波的动态测量模型;针对wMPS实际动态测量结果中的粗大误差,提出了一种基于卡尔曼滤波原理的粗大误差辨析和剔除方法;并通过仿真和实验验证卡尔曼滤波方法在解决wMPS动态测量问题中的正确性和有效性。5.重要工程应用研究。以面向航天GNC仿真实验为背景,对wMPS动态测量性能进行验证。通过现场条件下构建高精度测量场,采用多发射站间同步误差补偿方法和卡尔曼滤波方法,完成了现场条件下动态测量性能的验证。
[Abstract]:WMPS(workspace Measuring and Positioning system (wMPS(workspace Measuring and Positioning system) is a new type of large scale 3D coordinate measuring system based on photoelectric scanning. It has large range coverage, high degree of automation and strong anti-interference ability. At present, the static measurement performance and precision of wMPS have been studied systematically and comprehensively, however, In this paper, the dynamic measurement error model of the system is studied on the premise of optimizing the global netting orientation method. Based on this, the system dynamic measurement error is reduced by synchronous error compensation between multiple transmitting stations and Kalman filter model. Finally, the dynamic measurement performance of wMPS is improved. The main research contents are as follows: 1.The urgent need for advanced large-scale dynamic measurement technology in large-scale equipment manufacturing industry is summarized, and the advantages and limitations of various existing measurement methods are analyzed. The potential ability of wMPS in solving the problem of large scale dynamic measurement under field conditions is described. The dynamic measurement characteristics of wMPS are analyzed, and the effects of phase error and synchronization error on dynamic measurement are emphatically analyzed. In order to provide theoretical basis for improving the dynamic measurement performance, the construction of high-precision large-scale measurement field is the prerequisite to realize the dynamic performance of wMPS. Two kinds of netting orientation methods based on control field and combined adjustment based on relative constraint control are studied. The directional model and the method of obtaining the initial value of iteration are expounded, and the advantages and disadvantages of the two methods are analyzed. Finally, the feasibility and accuracy of the two methods are verified by experiments. This paper provides a high precision network structure foundation for wMPS dynamic measurement. Aiming at the problem of synchronous error compensation between multiple transmitting stations, the embedded SOPC processing system based on Microblaze is built in the signal processor. The multi-channel signal is triggered and collected under the same time datum, and the time of receiving information of each transmitting station is marked. Based on this, the Lagrangian interpolation method is introduced to realize the synchronization of measurement information between multiple transmitting stations. The synchronization error between multiple transmission stations is compensated and verified by relevant experiments, which improves the dynamic measurement accuracy .4.According to the motion characteristics of the target, the Kalman filter algorithm is introduced to further reduce the dynamic measurement error. A dynamic measurement model based on linear Kalman filter and extended Kalman filter is constructed, and a method of discriminating and eliminating gross error based on Kalman filter principle is put forward in view of the gross error in the actual dynamic measurement results of wMPS. The correctness and validity of Kalman filter method in solving wMPS dynamic measurement problem are verified by simulation and experiment. 5. The important engineering application research. The dynamic measurement performance of wMPS is verified by constructing a high-precision measurement field under field conditions, and the dynamic measurement performance is verified under field conditions by using synchronous error compensation method and Kalman filter method between multiple transmitting stations.
【学位授予单位】：天津大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：TG806

【参考文献】