基于机器视觉的插件式元器件插装后自动检测系统在PCBA过程中的应用

Application of Machine Vision Based Automatic Detection System for Plug-In Components after Insertion in PCBA Process

本文提出了一种基于视觉检测的自动化系统,旨在快速、准确地检测和分类插件式电子元器件插装后的错、漏、反、多、歪斜等缺陷。该系统利用高分辨率图像采集设备和先进的图像处理算法,实时检测和定位PCB板上的插件式电子元器件,并通过分析图像中的特征和模式,自动识别与分类缺陷,对不同缺陷开展针对性处理,大大提高了生产效率和产品质量。

This paper proposes an automated system based on visual inspection,aiming to quickly and accurately detect and classify defects such as errors,omissions,reversals,multiples,and skews in plug-in electronic components after insertion.This system utilizes high-resolution image acquisition equipment and advanced image processing algorithms to detect and locate plug-in electronic components on PCB boards in real-time.By analyzing the features and patterns in the images,defects are automatically identified and classified,and targeted processing is carried out for different defects,greatly improving production efficiency and product quality.