«上一篇/Previous Article|本期目录/Table of Contents|下一篇/Next Article»

《电镀与精饰》[ISSN:1001-3849/CN:12-1096/TG]

卷:

期数:

2026年01

页码:

18-24

栏目:

出版日期:

2026-01-31

文章信息/Info

Title:

Hessian matrix micro defect detection for surface images of electroplated copper foil

作者:

王艳华

(吉林建筑科技学院 计算机工程与人工智能学院,吉林 长春 130114)

Author(s):

WANG Yanhua

(School of Computer Engineering and Artificial Intelligence, Jilin University of Architecture and Technology, Changchun 130114, China)

关键词:

电镀铜箔; 表面微缺陷; 电磁超声; 全聚焦成像

Keywords:

electroplated copper foil;  surface micro defects;  electromagnetic ultrasound;  full focus imaging

分类号:

TP391.4；TQ153.1

文献标志码:

A

摘要:

电镀铜箔表面微缺陷尺寸微小，利用全聚焦成像可提升分辨率，由于不同类型的微缺陷尺寸和形态分布在一个较宽的范围内，而单一图像处理算法参数难以有效检测所有类型的缺陷，需要一种能自适应不同尺度的分析方法。对此，本文提出一种面向电镀铜箔表面成像的Hessian矩阵微缺陷检测方法。通过调控电镀液添加剂成分，制备了具有针孔与表面粗糙两类典型缺陷的可控样本及无缺陷对比样本。采用电磁超声全聚焦成像技术对样本进行检测，利用其横波模式对表面缺陷的高灵敏度，获取了高信噪比的缺陷图像数据；并针对成像结果中缺陷特征，提出了一种基于Hessian矩阵与多尺度分析的缺陷检测算法。该算法通过计算Hessian矩阵特征值实现点状与线状缺陷的增强，结合多尺度响应融合与余弦相似度计算，有效实现了复杂背景下的微缺陷精准识别。结果表明，所制备的缺陷样本特征鲜明，电磁超声TFM成像能清晰区分不同缺陷类型；所提出的缺陷检测方法在对比实验中显著优于对比方法，具有更高的检测精度与抗干扰能力，为电镀铜箔的工艺优化与在线质量检测提供了可靠的技术手段。

Abstract:

The size of micro defects on the surface of electroplated copper foil is very small, and the resolution can be improved by using fully focused imaging. However, due to the wide range of size and morphology distribution of different types of micro defects, a single image processing algorithm parameter is difficult to effectively detect all types of defects, and an analysis method that can adapt to different scales is needed. This article proposes a Hessian matrix micro defect detection method for surface imaging of electroplated copper foil. Controllable samples with typical defects of pinholes and surface roughness, as well as defect free comparative samples, were successfully prepared by regulating the composition of electroplating solution additives. Electromagnetic ultrasound fully focused imaging technology was used to detect the sample, and the high sensitivity of its transverse wave mode to surface defects was utilized to obtain defect image data with high signal-to-noise ratio. A defect detection algorithm based on Hessian matrix and multi-scale analysis was proposed to meet the demand for defect feature extraction in imaging results. This algorithm enhances point and line defects by calculating the Hessian matrix eigenvalues, and combines multi-scale response fusion and cosine similarity calculation to effectively achieve precise identification of micro defects in complex backgrounds. The experimental results show that the defect samples prepared in this paper have distinct characteristics, and electromagnetic ultrasound TFM imaging can clearly distinguish different types of defects. The proposed defect detection method is significantly superior to the comparative method in the comparative experiment, with higher detection accuracy and anti-interference ability, providing a reliable technical means for process optimization and online quality inspection of electroplated copper foil

常用功能

更新日期/Last Update: 2026-01-16