Fuzzy inference system to inspect coating in canmaking industry

P. Marino, V. Pastoriza, M. Santamaría, E. Martínez
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引用次数: 0

Abstract

The authors have been involved in developing an automated inspection system, based on machine vision, to improve the coating quality control in can ends of metal containers for fish food. In this work we present a fuzzy model building to make the acceptance/rejection decision for each can end from the information obtained by the vision system. In addition it is interesting to note that such model could be interpreted and supplemented by process operators. In order to achieve such aims, we use a fuzzy model due to its ability to favour the interpretability for many applications. Firstly, the easy open can end manufacturing process, and the current, conventional method for quality control of easy open can end repair coating, are described. Then, we show the machine vision system operations. After that, the fuzzy modeling, results obtained and their discussion are presented. Finally, concluding remarks are stated.
模糊推理系统在制罐工业涂料检测中的应用
作者参与开发了一种基于机器视觉的自动检测系统,以改善鱼食品金属容器罐头末端的涂层质量控制。在这项工作中,我们提出了一个模糊模型的建立,使每个可以结束的接受/拒绝决策从视觉系统获得的信息。此外,值得注意的是,这种模型可以由流程操作符进行解释和补充。为了实现这样的目标,我们使用模糊模型,因为它的能力有利于许多应用程序的可解释性。首先介绍了易开罐口的制造工艺,以及目前易开罐口修补涂层质量控制的常规方法。然后,我们展示了机器视觉系统的操作。在此基础上,给出了模糊建模的结果和讨论。最后,结束语。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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