基于机器视觉的烟支搭口夹杂缺陷在线检测方法

为解决卷烟生产中烟支搭口夹杂缺陷检测准确率低等问题，提出了一种基于机器视觉的搭口夹杂缺陷检测方法。在卷接机组检测轮和剔除轮位置分别安装高速相机，采集单支烟不同位置和角度的图像；采用均值滤波、灰度梯度计算等方法，先判断烟支搭口边缘，再判定搭口边缘区域是否存在夹杂缺陷；根据判定结果将缺陷烟支通过剔除阀剔除。应用该系统对杭州卷烟厂生产的2种规格卷烟进行测试，结果表明：正常工况下系统对烟支搭口夹杂检测准确率≥99.5%，漏检率<1%；异常工况下检测准确率≥99.0%，抗干扰能力强，检测处理时间≤6 ms。该技术可为提升烟支外观质量提供支持。

Online inspection of cigarette seam defects based on machine vision

In order to promote the inspection accuracy of cigarette seam impurities, small pieces of tobacco, dried glue and others, an inspection method based on machine vision was proposed. High-speed cameras were installed near the inspection drum and rejection drum in the cigarette maker separately to capture the images of each single cigarette from different positions and angles. Mean filtering and gray gradient calculation methods were used to determine the edges of cigarette seam, and then to determine whether there existed any impurities within the area enclosed by the edges. The cigarette with seam impurity was rejected through a rejection valve. The system was tested on cigarettes of two different specifications in Hangzhou Cigarette Factory. The results showed that under normal working conditions, the rejection accuracy for cigarettes with seam impurity was ≥99.5%, and the miss rate was < 1%; under abnormal working conditions, the rejection accuracy was ≥99.0%, the system showed high resistance to interference, the inspection time was ≤6 ms. This technology provides a support for improving the appearance quality of cigarettes.