摘要
为实现自动检测铁氧体湿压磁瓦外观缺陷,设计一种基于机器视觉的铁氧体湿压磁体外观检测设备。首先介绍系统结构和电气控制部分,接着根据铁氧体湿压磁体表面裂纹噪点多特点,采用多尺度灰度变换增强特征域对比度,并采用快速离散傅里叶变换准确定位缺陷位置,最后利用硬阀值分割图像,并比较灰度形态滤波和软形态混合滤波准确度。实验表明,软形态混合滤波更适用于多纹理的氧体湿压材料缺陷识别。
A machine vision-based appearance detection system is proposed for automatically detecting the appearance defects of wet-pressed ferrite magnets.Firstly,the system structure and electrical control part are introduced.Then,according to the characteristics of crack noise on the surface of wet-pressed ferrite magnets,multi-scale gray transform is used to enhance the contrast of feature domain,and fast discrete Fourier transform is used to locate the defect accurately.Finally,the image is segmented by hard threshold,and the accuracies of gray morphological filtering and soft morphological hybrid filtering are compared.Experiments show that the soft morphological hybrid filter is more suitable for multi-texture defect recognition of wet-pressed ferrite magnets.
作者
梁栋
顾杰宁
丁力
张陈
LIANG Dong;Gu Jiening;DING Li;ZHANG Chen(College of Mechanical Engineering,Jiangsu University of Technology,Changzhou 213001,Jiangsu,China)
出处
《陶瓷学报》
CAS
北大核心
2019年第5期675-680,共6页
Journal of Ceramics
基金
江苏省基础研究计划项目(BK20170135)
关键词
铁氧体湿压磁体
多尺度灰度变化
离散傅里叶变换
软形态混合滤波
wet-pressed ferrite magnet
multiscale gray level change
discrete Fourier transform
soft morphological hybrid filter
作者简介
通信联系人:梁栋(1989-),男,硕士,助理实验师。
