Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD

In this work, we present a novel 3D descriptor, Improved Dexel Representation (IDR), which assists to input holistic information from an engineering CAD model to Convolutional Neural Network (CNN) based manufacturing applications. The IDR carries the model's position, size, and surface informat...

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Veröffentlicht in:IEEE transactions on industrial informatics 2021-12, p.1-1
Hauptverfasser: Fu, Xingyu, Peddireddy, Dheeraj, Aggarwal, Vaneet, Jun, Martin Byung-Guk
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Jun, Martin Byung-Guk
description In this work, we present a novel 3D descriptor, Improved Dexel Representation (IDR), which assists to input holistic information from an engineering CAD model to Convolutional Neural Network (CNN) based manufacturing applications. The IDR carries the model's position, size, and surface information, which not only provides high resolution to small-scale local (machining) features but also has the potential to reconstruct the original CAD model. Data conversion algorithms between IDR and other CAD models (mesh and NURBS model) are efficient. CNNs with IDR input can largely improve the prediction accuracy compared to other 3D descriptors, which reaches 98.8\% in the modified Machining-Process-Identifier dataset and 100\% on the FeatureNet style 3-class dataset. IDR benefits both the manufacturing industry and other CAD-related deep learning applications in engineering fields.
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subjects 3D descriptor
Computational modeling
ComputerAided Design (CAD)
Convolutional Neural Network (CNN)
Convolutional neural networks
feature recognition
Machining
Manufacturing
Neural networks
Solid modeling
Three-dimensional displays
title Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD
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