A Physics-Informed Convolutional Neural Network with Custom Loss Functions for Porosity Prediction in Laser Metal Deposition

A Physics-Informed Convolutional Neural Network with Custom Loss Functions for Porosity Prediction in Laser Metal Deposition

Physics-informed machine learning is emerging through vast methodologies and in various applications. This paper discovers physics-based custom loss functions as an implementable solution to additive manufacturing (AM). Specifically, laser metal deposition (LMD) is an AM process where a laser beam m...

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Bibliographic Details
Main Authors: Erin McGowan, Vidita Gawade, Weihong (Grace) Guo
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Sensors
Subjects:
laser-based additive manufacturing
deep learning
in situ porosity detection
data fusion
inspection and quality control
sensing
Online Access:https://www.mdpi.com/1424-8220/22/2/494

Internet

https://www.mdpi.com/1424-8220/22/2/494

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