PredNet and CompNet: Prediction and High-Precision Compensation of In-Plane Shape Deformation for Additive Manufacturin
Zhen Shen; Shang XQ(商秀芹); Gang Xiong
2019-08
Conference NameIEEE International Conference on Automation Science and Engineering
Conference Date2019
Conference PlaceVancouver, Canada
Abstract

The error compensation for printed objects in additive manufacturing (AM) has always been one of the most critical problems. The precision control of the AM is usually more difficult than the subtractive manufacturing system, whose precision can reach the micron level easily by using a servo system. For the AM, there usually exist shrinkage and curling effects which lead to deformation. In this paper, we focus on the in-plane shape deformation problem, and we build the PredNet and CompNet, using deep neural networks for the error prediction and compensation. We test our methods on dental crown models. We generate deformed models by simulationofthetranslation,scalingdownandrotationdeformation. The minimum F1 scores of error prediction and compensation can be up to 0.982.

Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26143
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 AuthorGang Xiong
Affiliation中国科学院自动化研究所
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhen Shen,Shang XQ,Gang Xiong. PredNet and CompNet: Prediction and High-Precision Compensation of In-Plane Shape Deformation for Additive Manufacturin[C],2019.
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