Machine vision based in-process light-emitting diode chip mounting system
Machine vision based in-process light-emitting diode chip mounting system
复制标题
基于机器视觉的在线发光二极管芯片安装系统
DOI：
10.1177/0020294018786747
复制
发表时间：
2018
影响因子：
2
通讯作者：
Po
中科院分区：
文献类型：
--
作者：
Chao;You;Po
背景资料：本研究针对发光二极体晶片自动制程贴装线位置不确定性问题，提出一种以机器视觉为基础的方法。为了将微小的发光二极管芯片放置在印刷电路板的图案上，通过视觉辅助的在线反馈实现了高度精确的安装过程。方法：该系统由一个电荷耦合器件相机，六轴机械臂，和三角洲机器人。照明系统是在线机器视觉问题的关键点。因此，设计最佳的照明解决方案是机器视觉系统中最困难的部分之一，在这项研究中，研究了几种照明技术和实验。为了开始安装过程中，发光二极管芯片内的摄像机领域的目标被识别，并用于引导三角洲机器人的抓取区域的基础上校准的单应性变换。努力已经集中在基于机器视觉的印刷电路板上的芯片引脚和孔的特征提取领域。彼此的对应性由芯片引脚的位置和印刷电路板电路图案确定。图像采集是直接在线真实的时间。图像分析算法必须足够快以跟踪生产率。为了补偿发光二极管芯片贴装过程中的不确定性，视觉反馈策略结合不确定性补偿策略。结果：最后，发光二极管芯片被自动抓取并准确放置在所需位置。结论：进行了在线和离线实验，以研究视觉系统的性能与检测和安装发光二极管芯片。
Background: In this study, a machine vision–based method was developed for automated in-process light-emitting diode chip mounting lines with position uncertainty. In order to place the tiny light-emitting diode chips on the pattern of a printed circuit board, a highly accurate mounting process is achieved with online feedback of the visual assistance. Methods: The system consists of a charge-coupled device camera, a six-axis robot arm, and a delta robot. The lighting system is a critical point for the in-process machine vision problem. Hence, designing the optimal lighting solution is one of the most difficult parts of a machine vision system, and several lighting techniques and experiments are examined in this study. In order to commence the mounting process, the light-emitting diode chip targets inside the camera field were identified and used to guide the delta robot to the grabbing zone based on the calibrated homography transformation. Efforts have been focused on the field of machine vision–based feature extraction of the chip pins and the holes on the printed circuit board. The correspondence of each other is determined by the position of the chip pins and the printed circuit board circuit pattern. The image acquisition is achieved directly online in real time. The image analysis algorithm must be sufficiently fast to follow the production rate. In order to compensate for the uncertainty of the light-emitting diode chip mounting process, a visual feedback strategy in conjunction with an uncertainty compensation strategy is employed. Results: Finally, the light-emitting diode chip was automatically grabbed and accurately placed at the desired positions. Conclusion: On-line and off-line experiments were conducted to investigate the performance of the vision system with respect to detecting and mounting light-emitting diode chips.