CT理论与应用研究2025，Vol.34Issue(2)：235-243,9.DOI:10.15953/j.ctta.2024.237
基于YOLOv8与度量分析的三维BGA焊球缺陷检测方法
A Three-dimensional BGA Solder Ball Defect Detection Method Based on YOLOv8 and Metric Analysis
摘要
Abstract
With the increasing integration and miniaturization of electronic devices,the detection of solder ball defects in ball grid array(BGA)packaging has become extremely important.In this study,a three-dimensional(3D)defect detection method for BGA solder balls was proposed.Computed tomography(CT)scanning was used to reconstruct internal 3D images of BGA chips.The YOLOv8 algorithm was utilized to develop a 3D target detection model.The void size ratio in the training dataset was adjusted to enhance sensitivity to void defects.This method identified void defects in 3D BGA images and generated candidate targets.A defect size measurement algorithm was designed to segment the internal voids in the solder balls.The void ratio was calculated to identify defects that met predefined criteria.The measurement algorithm was integrated into the dataset construction process.This integration of automated defect labeling reduced the workload of 3D annotation.Experiments were conducted on a 3D BGA chip image dataset.This method achieved high detection rates and low false detection rates.These results validate the effectiveness and reliability of the proposed method.关键词
三维目标检测/BGA焊球/缺陷检测/缺陷度量/OTSU阈值分割Key words
3D object detection/BGA solder balls/defect detection/defect measurement/OTSU threshold segmentation分类
信息技术与安全科学引用本文复制引用
黄云飞,李璇,陈平..基于YOLOv8与度量分析的三维BGA焊球缺陷检测方法[J].CT理论与应用研究,2025,34(2):235-243,9.基金项目
国家重点研发计划(半导体器件封装质量智能检测关键技术研究与应用示范(2023YFE0205800)) （半导体器件封装质量智能检测关键技术研究与应用示范(2023YFE0205800）
山西省自然科学基金(基于X射线单投影的复杂产品装配正确性三维检测算法研究(202303021212207) （基于X射线单投影的复杂产品装配正确性三维检测算法研究(202303021212207）
基于能谱CT和深度迁移学习的致密油砂岩组分结构的定量表征方法研究(202103021224190)) （202103021224190）
山西省重点研发计划(复杂产品三维CT实时成像及缺陷智能识别(202302150401011)) （复杂产品三维CT实时成像及缺陷智能识别(202302150401011）
国家自然科学基金(面向航发叶片残芯影像表征的X射线多谱CT成像方法研究(62301508)). （面向航发叶片残芯影像表征的X射线多谱CT成像方法研究(62301508）
