Research On Key Technologies Of Vision System In Electronic Manufacturing Device

The electronic manufacturing devices are required to have better performance in speed and accuracy to meet the need of high density packaging, component size minimizing and high speed assembling. The visual inspection and alignment technology play a key role in achieving the high performance. In this dissertation, the problem of optics path design, optics inspection algorithm optimization and vision alignment algorithm development is addressed. A new on-the-fly vision system is designed to meet the requirements of high speed mounting of the components. The former on-the-fly vision systems are first analyzed and the virtues and shortcomings are explored. Unlike the stationary mirror method used in former designs, a retractable mirror is used to get the image of the component and the workpiece during the movements of the pick-up head. The implementation issues are further discussed. A fine adjustment mechanism is designed to correct the location and orientation of the camera, and a perspective distortion correction method is also proposed. A test framework for the vision processing algorithm is developed. The framework is designed with the ability of gray scale image acquisition, displaying, saving and processing. The optical inspection task and the corresponding algorithms in the electronic manufacturing are analyzed. The experiment and research work carried out in the framework are illustrated by 3 examples of real inspection tasks. On the experience of algorithms optimization, five principles are proposed for the design of the vision algorithms. A fast geometric characteristic-oriented algorithm is proposed for the cross fiducial alignment to meet the critical requirement of fast and accurate chip mounting. A hybrid spatial filtering method is improved to get a high quality bi-level image, then the randomized Hough transform and the least square method is taken to calculate accurate border line parameters. Experiments results demonstrate that the algorithm is fast and robust to the illumination changes, scale changes and partially hidden of the fiducial mark.