Nonlinear Deformation Prediction and Compensation for 3D Printing Based on CAE Neural Networks
Meihua Zhao1,2; Gang Xiong3,4; Xiuqin Shang1; Chang Liu5; Zhen Shen1,6; Huaiyu Wu1
2019-08-22
Conference Name2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)
Conference DateAugust 22-26, 2019
Conference PlaceVancouver, BC, Canada
Publisher2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)
Abstract

Although 3D printing technology has developed
rapidly in recent years, there are many problems to be solved.
The accuracy of the objects obtained by 3D printing is low
compared with subtractive manufacturing methods. There are
many factors that affect the errors, such as the shape of the
object, the properties of the material, and parameters in the
printing process. We takes Digital Light Processing (DLP) 3D
printing as an example in this paper and take the dental crowns
as the test category. We use the Convolutional Auto-Encoder
(CAE) architecture to make prediction and compensation for
the error of the 3D models directly. We use a simulation method
to obtain the data, and test on nonlinear deformation. The
results show that our network has a good ability to approximate
nonlinear deformation.

Indexed ByEI
Funding ProjectNational Natural Science Foundation of China[61773382] ; National Natural Science Foundation of China[61773381] ; National Natural Science Foundation of China[61533019] ; China Guangdong's ST Project[2017B090912001] ; Guangdong Science and Technology Department[2016B090910001]
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26149
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Corresponding AuthorZhen Shen
Affiliation1.the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences
2.the School of Artificial Intelligence, University of Chinese Academy of Sciences
3.Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences
4.the Cloud Computing Center, Chinese Academy of Sciences
5.the College of Computer Science, Sichuan University
6.the Intelligent Manufacturing Center, Qingdao Academy of Intelligent Industries
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Meihua Zhao,Gang Xiong,Xiuqin Shang,et al. Nonlinear Deformation Prediction and Compensation for 3D Printing Based on CAE Neural Networks[C]:2019 IEEE 15th International Conference on Automation Science and Engineering (CASE),2019.
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