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Parameter Identification and Refinement for Parallel PCB Inspection in Cyber-Physical-Social Systems | |
Yansong Cao1; Yutong Wang2![]() ![]() ![]() ![]() ![]() | |
发表期刊 | IEEE Transactions on Computational Social Systems
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ISSN | 2329-924X |
2023-12 | |
页码 | 1-10 |
通讯作者 | Wang, Xiao(xiao.wang@ahu.edu.cn) |
摘要 | Replacing manual inspection, automated optical inspection (AOI) equipment is widely used in printed circuit board (PCB) factories for automatic PCB defect segmentation. However, parameter refinement of AOI devices has gradually become an efficiency bottleneck in AOI usage, posing a highly challenging task. Since a large number of AOI parameters and different types of inspected objects make timely proper parameter refinement for clear images quite difficult. Considering this, we propose the concept of parallel PCB inspection in cyber–physical–social systems (CPSSs). Based on artificial systems, computational experiments, and parallel execution (ACP) theory with automatic parameter identification and refinement, we perform descriptive intelligence to build an artificial imaging system, obtain knowledge about the mapping relationships of parameter settings and imaging results, and realize automatic parameter identification given image input; conduct predictive intelligence to obtain image quality assessment results and maximize quality score for refinement strategies; and carry out prescriptive intelligence to guide parameter refinement for better imaging. This system could guide engineers proactively with constructive suggestions on parameter refinement when imaging failures occur, greatly reducing the training cost of engineers while improving work efficiency and work quality. To validate that our parallel PCB inspection could perform automatic AOI results evaluation without human participation, we evaluate it on distortion-free and different distortion images and confirm image quality score is positively associated with segmentation accuracy. |
关键词 | Imaging Inspection Image segmentation Image quality Hardware Training Software Automated optical inspection (AOI) parallel printed circuit board (PCB) inspection parameter identification parameter refinement |
DOI | 10.1109/TCSS.2023.3330762 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Optima Collaborative Research Project of Defect Detection Algorithm for Automated Optical Inspection-Phase II |
项目资助者 | Optima Collaborative Research Project of Defect Detection Algorithm for Automated Optical Inspection-Phase II |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Cybernetics ; Computer Science, Information Systems |
WOS记录号 | WOS:001170469200001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
国重实验室规划方向分类 | 实体人工智能系统感认知 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57290 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
通讯作者 | Jiangong Wang |
作者单位 | 1.the Faculty of Innovation Engineering, Macau University of Science and Technology 2.the Institute of Automation, Chinese Academy of Sciences 3.the China Institute of Aviation Systems Engineering 4.the School of Artificial Intelligence, Anhui University |
推荐引用方式 GB/T 7714 | Yansong Cao,Yutong Wang,Jiangong Wang,et al. Parameter Identification and Refinement for Parallel PCB Inspection in Cyber-Physical-Social Systems[J]. IEEE Transactions on Computational Social Systems,2023:1-10. |
APA | Yansong Cao,Yutong Wang,Jiangong Wang,Yonglin Tian,Xiao Wang,&Fei-Yue Wang.(2023).Parameter Identification and Refinement for Parallel PCB Inspection in Cyber-Physical-Social Systems.IEEE Transactions on Computational Social Systems,1-10. |
MLA | Yansong Cao,et al."Parameter Identification and Refinement for Parallel PCB Inspection in Cyber-Physical-Social Systems".IEEE Transactions on Computational Social Systems (2023):1-10. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Parameter_Identifica(2150KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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