利用图像识别方法改进再制造过程。机械部分的应用

Mitja Kos
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引用次数: 0

摘要

本文描述了在执行再制造过程的公司中使用、构建和实施图像识别系统的可能性。它是基于在威伯科雷曼解决方案的帮助下准备的论文。测试使用的是该公司再制造的零件之一——一个歧管。研究重点是对所获得的图像识别模型的不同变体,以识别可能影响其有效性和在实际工作条件下可能应用的差异。构建模型的环境是Jupyter Notebook,并实现了卷积神经网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Remanufacturing process improvement by image recognition methods. Application of the mechanical part
The paper describes the possibility of using, building, and implementing an image recognition system in a company performing remanufacturing processes. It is based on a thesis prepared with the help of Wabco Reman Solutions. The tests were conducted using one of the parts remanufactured by the company – a manifold. The research focuses on different variants of the obtained image recognition models in order to identify differences that may affect their effectiveness and possible application in real work conditions. The environment used to build the models is Jupyter Notebook, and convolutional neural networks were implemented.
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