CASIA OpenIR
A Learning-Based Framework for Error Compensation in 3D Printing
Shen, Zhen1,2; Shang, Xiuqin1; Zhao, Meihua1,3; Dong, Xisong1; Xiong, Gang1,4; Wang, Fei-Yue1
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
ISSN2168-2267
2019-11-01
Volume49Issue:11Pages:4042-4050
Corresponding AuthorXiong, Gang(gang.xiong@ia.ac.cn)
AbstractAs a typical cyber-physical system, 3D printing has developed very fast in recent years. There is a strong demand for mass customization, such as printing dental crowns. However, the accuracy of the 3D printed objects is low compared with traditional methods. The main reason is that the model to be printed is arbitrary and usually the quantity is small. The deformation is affected by the shape of the object and there is a lack of a universal method for the error compensation. It is neither easy nor economical to perform the compensation manually. In this paper, we present a framework for the automatic error compensation. We obtain the shape by technologies such as 3D scanning. And we use the "3D deep learning" method to train a deep neural network. For a specific task, such as dental crown printing, the network can learn the function of deformation when a large amount of data is used for training. To the best of our knowledge, this is the first application of the deep neural network to the error compensation in 3D printing. And we propose the "inverse function network" to compensate for the error. We use four types of deformations of the dental crowns to verify the performance of the neural network: 1) translation; 2) scaling up; 3) scaling down; and 4) rotation. The convolutional AutoEncoder structure is employed for the end-to-end learning. The experiments show that the network can predict and compensate for the error well. By introducing the new method, we can improve the accuracy with little need for increasing the hardware cost.
Keyword3D printing additive manufacturing cyber-physical system (CPS) deep learning error compensation
DOI10.1109/TCYB.2019.2898553
WOS KeywordSYSTEMS
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61773382] ; National Natural Science Foundation of China[61773381] ; National Natural Science Foundation of China[61872365] ; National Natural Science Foundation of China[61533019] ; National Natural Science Foundation of China[61702519] ; Chinese Guangdong's ST Project[2017B090912001] ; Chinese Guangdong's ST Project[2016B090910001] ; Beijing Natural Science Foundation[4182065] ; Chinese Hunan's ST Project[20181040] ; Beijing Ten Dimensions Technology Company Ltd. ; Institute of Automation, Chinese Academy of Sciences ; Dongguan's Innovation Talents Project
Funding OrganizationNational Natural Science Foundation of China ; Chinese Guangdong's ST Project ; Beijing Natural Science Foundation ; Chinese Hunan's ST Project ; Beijing Ten Dimensions Technology Company Ltd. ; Institute of Automation, Chinese Academy of Sciences ; Dongguan's Innovation Talents Project
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000476811000018
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/27813
Collection中国科学院自动化研究所
Corresponding AuthorXiong, Gang
Affiliation1.Chinese Acad Sci, Beijing Engn Res Ctr Intelligent Syst & Technol, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Qingdao Acad Intelligent Ind, Intelligent Mfg Ctr, Qingdao 266109, Shandong, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China
4.Chinese Acad Sci, Cloud Comp Ctr, Dongguan 523808, Peoples R China
Recommended Citation
GB/T 7714
Shen, Zhen,Shang, Xiuqin,Zhao, Meihua,et al. A Learning-Based Framework for Error Compensation in 3D Printing[J]. IEEE TRANSACTIONS ON CYBERNETICS,2019,49(11):4042-4050.
APA Shen, Zhen,Shang, Xiuqin,Zhao, Meihua,Dong, Xisong,Xiong, Gang,&Wang, Fei-Yue.(2019).A Learning-Based Framework for Error Compensation in 3D Printing.IEEE TRANSACTIONS ON CYBERNETICS,49(11),4042-4050.
MLA Shen, Zhen,et al."A Learning-Based Framework for Error Compensation in 3D Printing".IEEE TRANSACTIONS ON CYBERNETICS 49.11(2019):4042-4050.
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