CASIA OpenIR  > 学术期刊  > IEEE/CAA Journal of Automatica Sinica
Industry-oriented Detection Method of PCBA Defects Using Semantic Segmentation Models
Yang Li; Xiao Wang; Zhifan He; Ze Wang; Ke Cheng; Sanchuan Ding; Yijing Fan; Xiaotao Li; Yawen Niu; Shanpeng Xiao; Zhenqi Hao; Bin Gao; Huaqiang Wu
Source PublicationIEEE/CAA Journal of Automatica Sinica
AbstractAutomated optical inspection (AOI) is a significant process in printed circuit board assembly (PCBA) production lines which aims to detect tiny defects in PCBAs. Existing AOI equipment has several deficiencies including low throughput, large computation cost, high latency, and poor flexibility, which limits the efficiency of online PCBA inspection. In this paper, a novel PCBA defect detection method based on a lightweight deep convolution neural network is proposed. In this method, the semantic segmentation model is combined with a rule-based defect recognition algorithm to build up a defect detection framework. To improve the performance of the model, extensive real PCBA images are collected from production lines as datasets. Some optimization methods have been applied in the model according to production demand and enable integration in lightweight computing devices. Experiment results show that the production line using our method realizes a throughput more than three times higher than traditional methods. Our method can be integrated into a lightweight inference system and promote the flexibility of AOI. The proposed method builds up a general paradigm and excellent example for model design and optimization oriented towards industrial requirements.
KeywordAutomated optical inspection (AOI) deep learning defect detection printed circuit board assembly (PCBA) semantic segmentation
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Document Type期刊论文
Collection学术期刊_IEEE/CAA Journal of Automatica Sinica
Recommended Citation
GB/T 7714
Yang Li,Xiao Wang,Zhifan He,et al. Industry-oriented Detection Method of PCBA Defects Using Semantic Segmentation Models[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(6):1438-1446.
APA Yang Li.,Xiao Wang.,Zhifan He.,Ze Wang.,Ke Cheng.,...&Huaqiang Wu.(2024).Industry-oriented Detection Method of PCBA Defects Using Semantic Segmentation Models.IEEE/CAA Journal of Automatica Sinica,11(6),1438-1446.
MLA Yang Li,et al."Industry-oriented Detection Method of PCBA Defects Using Semantic Segmentation Models".IEEE/CAA Journal of Automatica Sinica 11.6(2024):1438-1446.
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