基于协调的注意引导信息融合的PCB插件接接头缺陷检测方法
Wenbin Chen1, Zheng Wang2, Hongchao Zhao3
1School of Electrical Engineering, Chongqing University of Science and Technology, Chongqing, 404100, People's Republic of China. chenwb@cqust.edu.cn.
Scientific reports
|August 27, 2024
概括
本研究介绍了一种改进的YOLOv3算法,用于检测印刷电路板 (PCB) 接缺陷. 增强方法实现了更高的准确性和更低的错误报警率,这对于电子产品质量控制至关重要.
科学领域:
- 电子工程 电子工程
- 计算机视觉 计算机视觉
- 质量控制 质量控制 质量控制
背景情况:
- 印刷电路板 (PCB) 是电子设备的基础.
- 有效的PCB缺陷检测对于产品质量保证至关重要.
- 现有的算法难以平衡精度,低误报率和速度.
研究的目的:
- 开发一种高精度,低错误报警和高速的PCB插电缺陷检测方法.
- 增强现有的缺陷检测算法的功能.
主要方法:
- 利用以注意为导向的金字塔结构来实现上下文信息融合.
- 整合了一个协调的注意网络来校准功能并减少冗余.
- 在Darknet53的骨干中集成Atrous空间金字塔聚合 (ASPP),用于多层次的特征提取.
主要成果:
- 增强的网络实现了96.43%的平均检测准确度,比94.45%有所改善.
- 拟议的方法在PCB插件接器缺陷检测方面表现出卓越的性能.
- 这些改进解决了现有算法在精度,错误报警率和速度方面的局限性.
结论:
- 改进的基于YOLOv3的方法非常适合PCB插件接器缺陷检测.
- 空间卷积聚合和信息融合的整合显著提高了检测性能.
- 这种方法有助于在电子制造业更强大的质量控制.
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