为减少因封酒环缺陷导致酒质量变差的问题,提高缺陷检测效率,需对封酒环在线缺陷检测方法展开研究与开发。根据封酒环结构、位置与瓶盖内径、深度等特点,研发一种基于机器视觉双视场双工位协同在线检测系统。针对封酒环轮廓缺陷在二维信息中难以提取的问题,提出将封酒环轮廓二维信息转换成一维向量,在此基础上应用一维向量理论对其缺陷进行分析与处理,并采用小波模极大值法进行缺陷提取与判定。实验结果表明该系统可有效检测封酒环轮廓任意位置缺陷,检测精度达到99.89%。与手工检测相比,轮廓信息经维度转换后,检测效率提高6倍以上,满足现场实际生产和预期研发要求,为封酒环无损在线检测提供新的途径。

To address the problem of poor wine quality caused by wine seal ring defects and improve defect detection efficiency, an online detection method for wine seal ring defects is developed. According to the structure and position of the wine seal rings and the inner diameter and depth of the bottle caps, an online detection system based on machine vision dual-field and dual-station collaboration methods is proposed. Given that it is difficult to extract the contour defects of wine seal rings from two-dimensional information, we transform the two-dimensional information of a wine seal ring contour into an one-dimensional vector. Then, the one-dimensional vector theory is applied to analyze and deal with the defects, and the wavelet modulus maxima method is used to extract and determine them. The experimental results show that the system can effectively detect defects at any position of a wine ring and that its detection accuracy is 99.89%. The efficiency of the method described in this paper is six times higher than that of manual inspection. It meets the requirements of production and expected R&D, and provides a new technique for the non-destructive online detection of wine seal ring defects.