基于改进的YOLOX,设计用于糊印刷缺陷的智能检查系统
Defeng Kong1, Xinyu Hu1, Junwei Zhang1
1School of Mechanical Engineering, Hubei University of Technology, 28 Nanli Road, Hongshan District, Wuhan City, Hubei Province 430068, China.
iScience
|March 4, 2024
概括
这项研究增强了糊检查 (SPI) 系统,用于检测类似的缺陷. 改进的YOLOX模型达到90.33%的精度,为高精度的SPI提供了可行的解决方案.
科学领域:
- 制造业 工程 制造工程
- 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:
- 目前的糊检查 (SPI) 系统在高精度和智能检测类似缺陷方面存在局限性.
- 电子制造业需要先进的自动化检查系统.
研究的目的:
- 设计一个改进的智能检测系统,用于糊类似的缺陷.
- 提高SPI系统的准确性和智能性.
主要方法:
- 阶段调制配置测量技术与改进的YOLOX智能检测系统的整合.
- 开发一个改进的YOLOX深度模型,结合s-mosica和kt-iou算法.
主要成果:
- 拟议的s-mosica和kt-iou算法有效地提高了印刷糊缺陷的检测精度.
- 组合的YOLOX模型实现了最高的检测准确率90.33%.
- 开发的系统在相同的场景中表现优于现有的算法.
结论:
- 增强的YOLOX系统为设计高精度SPI系统提供了有效和可行的参考.
- 该研究表明,用于糊印刷的自动缺陷检测取得了重大进展.
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