| 魏继晨,万发雨,夏敏峰,石丽媛,陈佳文,陈晓禾.基于双目视觉的器件带电放电自动化测试方法研究[J].电子测量与仪器学报,2026,40(6):290-298 |
| 基于双目视觉的器件带电放电自动化测试方法研究 |
| Research on automatic tester for charged and discharged devicesbased on binocular recognition |
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| DOI： |
| 中文关键词: 静电放电 带电器件模型 双目视觉 图像处理 目标检测 |
| 英文关键词:electrostatic discharge charged device model binocular vision image processing object detection |
| 基金项目:北京市自然科学基金项目（L233002）资助 |
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| Author | Institution |
| Wei Jichen | School of Electronic and Information Engineering, Nanjing University of Information Science and Technology,
Nanjing 210044, China |
| Wan Fayu | School of Electronic and Information Engineering, Nanjing University of Information Science and Technology,
Nanjing 210044, China |
| Xia Minfeng | School of Electronic and Information Engineering, Nanjing University of Information Science and Technology,
Nanjing 210044, China |
| Shi Liyuan | School of Electronic and Information Engineering, Nanjing University of Information Science and Technology,
Nanjing 210044, China |
| Chen Jiawen | School of Electronic and Information Engineering, Nanjing University of Information Science and Technology,
Nanjing 210044, China |
| Chen Xiaohe | School of Artificial Intelligence, China University of Petroleum, Beijing 102249, China |
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| 摘要点击次数: 55 |
| 全文下载次数: 16 |
| 中文摘要: |
| 针对带电器件模型(CDM)的静电放电(ESD)测试中探针与芯片封装pad快速定位的难题，提出一种基于双目视觉的探针 封装pad快速对齐方法。首先构建一组针对芯片封装的图像数据集，使用轻量化的L-YOLOv8n算法训练模型作为前端识别待测芯片，然后通过图像处理模块完成对pad的亚像素级分割与定位，基于视差和立体匹配获取pad的精准三维坐标信息，最后将信息发送到CDM ESD测试系统的主控板中控制步进电机实现探针与pad的快速精准对齐。实验结果表明，系统在小样本训练条件下对BGA、SOP等多种封装芯片的mAP在99%以上，并实现对pad的完整识别与三维坐标的精准提取，在水平二维方向定位精度达0.01 mm，深度方向精度为0.1 mm。同时，该系统具备成本低和环境适应性强的优势，无需人工将探针与pad对齐进行测试，仅利用摄像设备与运动控制模块即可完成探针-pad的快速精准对齐，部署方便，适用于多场景、多种芯片封装类型的CDM测试。 |
| 英文摘要: |
| A binocular vision based probe package pad rapid alignment technique is proposed to address the challenge of rapid positioning between probes and chip packaging pad in electrostatic discharge (ESD) testing of charged device models (CDM). Firstly, a set of image datasets for chip packaging is constructed, and a lightweight L-YOLOv8n algorithm is used to train the model as the front-end recognition of the chip under test. Then, the sub-pixel segmentation and positioning of the pad are completed through the image processing module, and the three-dimensional coordinate information of the pad is accurately obtained based on visual difference and stereo matching. Finally, the information is sent to the main control board of the CDM ESD testing system to control the stepper motor and achieve fast and accurate alignment between the probe and pad. The experimental results show that the system has an mean average precision (mAP) of over 99% for various packaged chips such as BGA and SOP under small sample training conditions, and achieves complete recognition of pad and accurate extraction of three-dimensional coordinates. The positioning accuracy in the horizontal two-dimensional direction reaches 0.01 mm, and the depth direction accuracy is 0.1 mm. At the same time, the system has significant advantages in low cost and strong environmental adaptability, without the need for manual alignment of probes with pad for testing. The rapid and accurate alignment of probe pad can be completed with only camera equipment and motion control modules, which is easy to deploy and suitable for CDM testing in multiple scenarios and various chip packaging types. |
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