【作者】 朱嘉；

【导师】 李醒飞；

【作者基本信息】 天津大学 ， 测试计量技术及仪器， 2010， 博士

【摘要】 随着航空航天、造船、汽车和模具制造等现代工业的飞速发展,对产品性能、外形等方面的要求越来越高。快速地从复杂形状的工件中获得高精度的坐标数据具有广泛的应用,如检测过程中的工件定位和自动化标定,敏捷制造,以及逆向工程中的快速产品设计。这也对测量系统的精度、速度和自动化水平提出了更高的要求。使用单一传感器和传统的正交坐标系的测量系统在测量范围、测量精度和工作效率等方面总是存在着这样或那样的不足。近年来,多传感器集成和多坐标组合的测量系统逐渐成为国内外研究的热点并取得了一定的进展,但仍存在许多不足,特别是在多传感器标定、多坐标系统一和信息的智能化集成等方面。本文对一种基于视觉与触觉集成传感的多坐标组合测量系统进行了研究,主要研究工作包括:1.针对光源、物体表面散射特性等影响轮廓成像质量的关键因素,提出了使用远心镜头和平行光源的基于平行投影的图像采集系统。实验结果显示该图像采集系统能够有效提高轮廓图像的成像质量,因而有利于轮廓测量。2.针对θFXZ结构形式的多坐标系统建立了其准刚体运动模型,提出了基于激光干涉仪的直线运动部件各单项几何误差的检定方法,并据此模型对系统的几何误差作补偿。提出了通过瞄准标记点的分度台综合性能的评定方法,实现了系统坐标系的统一。3.分别建立了摄像机和触发式测头的数学理论模型,提出了快速高精度的摄像机主动视觉标定方法,基于预行程误差理论模型的触发式测头标定方法,和两种测头的联合标定方法。通过各自模型的参数辨识最终解决了多传感器集成的配准问题。4.研究了测量图像处理中的多图像平均的图像滤波方法,基于IVFS的模糊指数最大原则的灰度阈值分割算法,基于数学形态学的边缘检测算子,并通过二次曲线拟合实现了测量图像的快速亚像素定位,定位精度为0.1pixel。5.对视觉与触觉传感信息集成进行了研究。分析了传感器的选择方法。根据边界曲线法矢的变化规律,通过特征映射完成了曲线基元的自动分割。给出了具有约束条件的最小二乘原理的基元参数估计方法。分析了边界特征指导下的测量规划方法。以实例说明了多传感器集成在工件定位和联合测量上的应用。更多还原

【Abstract】 The requirements on the performance and shape of products are increasing, along with the rapid development of modern industry such as aerospace, shipbuilding, automobile, mould manufacturing etc. Rapid and high accuracy coordinate data acquisition from complicate workpiece has wide application to many fields, such as loacation and automated cablication of parts in detection process, agile manufacturing, rapid product design in reverse engineering. It also puts forward higher requirements for the accuracy, speed and automation level of the measuring system. Conventional single-sensor and orthogonal coordinate system has these or those shortages in aspects of measuring range, accuracy and efficiency etc. Recently, multiple-sensor integration and multi-axis measuring system has become a research hot spot and has achieved some progress, but there are still some problems to be solved, especially in aspects of calibration of multiple-sensor, multi-coordinates unification and intelligent imformation integration.In this study, a multi-axis inspection system based on integrated vision and touch sensing is studied. The main research work includes:1. An image acquisition system featured with parallel projection achieved by the use of telecentric optics and parallel illumination is proposed, aiming at illumination, scattering characteristics, and other factors which affect profile imaging quality. Experimental results show that the proposed image acquisition system can efficiently improve the profile imaging quality and is beneficial to profile measurement.2. According to the structure form ofθFXZ for a multi-axis system, a pseudo-rigid body kinematic model is built. A verification method based on laser interferometer for each single geometric error of linear moving components is proposed and used for geometric error compensation. An evaluation method of comprehensive properties for turning table by aming at marker points is proposed, achieving the unification of system coordinate.3. Mathematical theory models of camera and touch trigger probe are built respectively. A rapid and high-precision camera calibaration technique based on active vision, a touch trigger probe calibration method based on pre-travel error model, and a combined calibration method for these two sensors are analyzed in detail. The registration problem in multi-sensor integration is finally solved. 4. Image filtering algorithm using average of multiple images, gray threshold segmentation based on IVFS Maximum fuzzy exponential principle, edge detection operator based on mathematical morphology are studied. Fast sub-pixel location of measuring image is achieved by conic fitting. The positioning accuracy of 0.1 pixels is attained.5. Information integration of vision and touch sensing is studied. Sensor selection strategy is analyzed firstly. Automatic segmentation of curve primitive of is completed by feature mapping, according to the change law of the normal vector of boundary curve. A primitive parameter estimation method based on least square principle with constraint condition is given then. Measuring planning guided by boundary feature is analyzed. Applications of multiple-sensor integration in workpiece localization and combined measurement are illustrated with examples finally.更多还原