A YOLO-based computer vision heat dissipation adhesive defect intelligent detection system
By using a YOLO-based computer vision system, combined with multimodal image acquisition and optical rendering technology, the problems of material adaptability and real-time performance in thermal adhesive inspection were solved, achieving efficient and accurate defect detection.
CN122415529APending Publication Date: 2026-07-17EAST CHINA NORMAL UNIV
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Patent Information
- Application Number
- CN202610543215.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-23
- Publication Date
- 2026-07-17
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Figure CN122415529A_ABST
Abstract
本发明提出了一种基于YOLO的计算机视觉散热胶缺陷智能检测系统，包括多模态采集单元，所述多模态采集单元通过可见光相机和近红外相机同步采集散热胶多模态图像；YOLO处理架构，所述YOLO处理架构内设有供多模态图像进行缺陷检测和修正的特征融合模块，所述特征融合模块内置有缺陷算法和部署单元，所述缺陷算法集成小目标检测技术和颜色缺陷分析技术综合分析散热胶缺陷，涉及散热胶缺陷检测技术领域。本发明通过同步采集400‑700nm的可见光与850‑1550nm的近红外光的双光谱图像，利用材料光学特性差异增强缺陷辨识，并且针对微小缺陷增加了P2高分辨率特征层，并优化了级别为4×4dpi的锚框尺寸，最后通过K‑means++聚类匹配小目标分布，提升了散热胶画质缺陷的修补和修复。
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