覆膜圆柱锂电池圆周面破膜缺陷检测方法研究  

Research on Detection Method of Broken Film Defect on Circumferential Surface of Coated Cylindrical Lithium Battery

作　　者：张思宽 苑玮琦[1,2] Zhang Sikuan;Yuan Weiqi(Computer Vision Group,Shenyang University of Technology,Shenyang,China;Key Laboratory of Machine Vision of Liaoning Province,Shenyang,China)

机构地区：[1]沈阳工业大学视觉检测技术研究所,辽宁沈阳 [2]辽宁省机器视觉重点实验室,辽宁沈阳

出　　处：《科学技术创新》2024年第23期65-68,共4页Scientific and Technological Innovation

摘　　要：破膜缺陷是覆膜圆柱锂电池圆周面最常见的一种缺陷,为产品的运输使用带来危害。因此,电池制造商需对电池进行圆周面破膜缺陷检测并筛选。针对电池常规出厂检测中对圆周面破膜缺陷检测的准确率较低的问题,设计了一种基于机器视觉的缺陷检测算法,首先对图像进行灰度水平校正,然后基于组合曲线段绝对幅值进行特征提取,最后通过电池灰度特征进行缺陷筛选。对图库进行测试,测试结果表明该算法能有效检测电池圆周面破膜缺陷。Broken film defect is the most common defect on the circumferential surface of coated cylindrical lithium batteries,which brings harm to the transportation and use of products.Therefore,it is necessary for battery manufacturers to detect and screen the broken film defects on circumferential surface of batteries.In view of the low accuracy of the detection of the broken film defects on circumferential surface in the conventional factory leaving inspections of batteries,a defect detection algorithm based on machine vision is designed.Firstly,the gray values of the image are horizontally corrected,and then the features are extracted based on absolute amplitude of combined curve segments.Finally,the defects are screened through the grayscale features of the battery.The test results of the library show that the algorithm can effectively detect the broken film defects on the circumferential surface of the batteries.

关 键 词：覆膜圆柱锂电池 破膜缺陷 组合曲线段绝对幅值 机器视觉 

分 类 号：TM912[电气工程—电力电子与电力传动]