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冷冲压阀片表面压痕精确检测方法

Accurate Detection Method for Surface Indentation of Cold Stamping Valve

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摘要

亮光构件表面缺陷引起的微小形状突变能够通过反射条纹的畸变凸显,因此反射条纹技术可应用于反光物体的表面质量检测。提出了一种基于反射条纹图像的冷冲压阀片表面压痕机器视觉检测方法,通过该方法提取阀片的条纹图像信息,并进行缺陷特征的自动识别。采用滤波去噪和多尺度Retinex算法等系列预处理方法提高图像质量,通过条纹中心线、子窗口像素和及投影向量等特征参量的选择降低计算的复杂度,增加计算系统的稳健性。实验结果表明:基于反射条纹图像的阀片表面压痕检测方法具有高精度、高效率等特点,实现了阀片表面细微压痕的有效识别,识别精度可达0.1 mm,检测效率(单张检测目标耗时2 s)可以满足阀片生产线的实际在线检测需求。

Abstract

The slight sudden changes in the surface of metal object can be highlighted by the distortion of reflection stripes. Therefore, the reflection stripe technique can be applied in the surface inspection of reflective objects. We propose a machine vision detection method for the surface indentation of cold stamping valves based on reflection stripe image. Along the way, stripe image information of cold stamping valves is extracted, and defect features are recognized automatically. A series of preprocessing methods, such as noise filtration and multi-scale Retinex algorithms, are adopted to improve the image quality. Characteristic parameters, such as fringe-centerlines, sum of pixels, and projection vectors in child windows, are selected to reduce the computation complexity and improve the robustness of the computing system. The experimental results show that this detection method for the surface indentation of cold stamping valves based on reflection stripe image has high accuracy and high efficiency. This method can achieve effective identification of subtle indentation on the surface of cold stamping valves to an accuracy of 0.1 mm, and detection time efficiency (one valve takes 2 seconds) meets the online detection demand for the cold stamping valve production line.

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中图分类号:TP391.4

DOI:10.3788/aos201838.0815013

所属栏目:“机器视觉检测与应用”专题

基金项目:国家自然科学基金青年科学基金(11504383)

收稿日期:2018-01-05

修改稿日期:2018-03-21

网络出版日期:2018-03-25

作者单位    点击查看

郭凤霞:中国科学院合肥物质科学研究院应用技术研究所, 安徽 合肥 230088
乌云:中国科学院合肥物质科学研究院应用技术研究所, 安徽 合肥 230088
李滨:中国科学院合肥物质科学研究院应用技术研究所, 安徽 合肥 230088
戚俊:中国科学院合肥物质科学研究院应用技术研究所, 安徽 合肥 230088

联系人作者:乌云(wuyun@rntek.cas.cn); 郭凤霞(guofengxia@126.com);

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引用该论文

Guo Fengxia,Wu Yun,Li Bin,Qi Jun. Accurate Detection Method for Surface Indentation of Cold Stamping Valve[J]. Acta Optica Sinica, 2018, 38(8): 0815013

郭凤霞,乌云,李滨,戚俊. 冷冲压阀片表面压痕精确检测方法[J]. 光学学报, 2018, 38(8): 0815013

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