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A particle swarm optimization approach for components placement inspection on printed circuit boards

机译:一种粒子群优化方法,用于印刷电路板上的零件放置检查

摘要

The importance of the inspection has been magnified by the requirements of the modern manufacturing environment. In electronics mass-production manufacturing facilities, especially in the printed circuit board (PCB) industry, 100% quality assurance of all work-in-process and finished goods is required in order to reduce the scrap costs and re-work rate. One of the challenges for PCB inspection is in the use of a surface mount device (SMD) placement check. Missing, misaligned or wrongly rotated components are the critical causes of defects. To prevent the PCB from having these defects, inspection must be done before the solder reflow process commences, otherwise, everything will be too late. The research reported in this paper concentrates on automatic object searching techniques, in a grey-scale captured image, for locating multiple components on a PCB. The presented approach includes the normalized cross correlation (NCC) based multi-template matching (MTM) method. The searching process has been carried out by using the proposed accelerated species based particle swarm optimization (ASPSO) method and the genetic algorithm (GA) approach as a reference. The experimental results of the ASPSO-based MTM approaches are reported.
机译:现代制造环境的要求已放大了检查的重要性。在电子批量生产制造设施中,尤其是在印刷电路板(PCB)行业中,要求所有在制品和制成品的质量保证为100%,以减少报废成本和返工率。 PCB检查的挑战之一是使用表面安装器件(SMD)放置检查。丢失,未对准或错误旋转的组件是造成缺陷的关键原因。为了防止PCB出现这些缺陷,必须在回流焊工艺开始之前进行检查,否则一切都为时已晚。本文报道的研究集中在灰度捕获图像中的自动对象搜索技术上,用于在PCB上定位多个组件。提出的方法包括基于归一化互相关(NCC)的多模板匹配(MTM)方法。搜索过程已通过使用所提出的基于加速物种的粒子群优化(ASPSO)方法和遗传算法(GA)方法进行了参考。报告了基于ASPSO的MTM方法的实验结果。

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