Research on Automated Defect Classification Based on Visual Sensing and Convolutional Neural Network-Support Vector Machine for GTA-Assisted Droplet Deposition Manufacturing Process

Research on Automated Defect Classification Based on Visual Sensing and Convolutional Neural Network-Support Vector Machine for GTA-Assisted Droplet Deposition Manufacturing Process

This paper proposes a novel metal additive manufacturing process, which is a composition of gas tungsten arc (GTA) and droplet deposition manufacturing (DDM). Due to complex physical metallurgical processes involved, such as droplet impact, spreading, surface pre-melting, etc., defects, including la...

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Bibliographic Details
Main Authors: Chen Ma, Haifei Dang, Jun Du, Pengfei He, Minbo Jiang, Zhengying Wei
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Metals
Subjects:
gas tungsten arc (GTA)
droplet deposition manufacturing (DDM)
visual sensing
defect classification
convolutional neural network-support vector machine (CNN-SVM)
Online Access:https://www.mdpi.com/2075-4701/11/4/639

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