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通过使用深度神经网络进行表面缺陷分类来控制碳外观组件的质量

Andrea Silenzi1, Vincenzo Castorani2, Selene Tomassini1

  • 1Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
概括

这项研究表明,深度神经网络可以使用常规图像对碳纤维部件的表面缺陷进行分类,达到97%的准确性. 这使得智能工厂能够在没有专门设备的情况下进行质量控制.

关键词:
在CFRP的基础上.工业4.0 工业4.0 工业4.0 工业4.0 工业4.0 是什么?碳纤维增强聚合物的聚合物.深度学习是一种深度学习.质量控制质量控制质量控制转移学习转移学习

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