Automatic quality monitoring of two-photon printed devices based on deep learning

Lijun Men; Ningning Hu; Yucheng Deng; Wenjun Zhang; Ruixue Yin

doi:10.1117/12.2684914

19 October 2023 Automatic quality monitoring of two-photon printed devices based on deep learning

Lijun Men, Ningning Hu, Yucheng Deng, Wenjun Zhang, Ruixue Yin

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127094B (2023) https://doi.org/10.1117/12.2684914
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

Two-photon 3D printing technology is an additive manufacturing technology that uses the two-photon absorption process of near-infrared radiation to create a three-dimensional micro-nano scale structure with extremely high resolution. However, in the preparation process of two-photon printing, the laser parameters for inducing photopolymerization have a huge impact on the quality of the polymer structure. Therefore, monitoring the quality of the device during the manufacturing process and rationally optimizing the laser parameters are of great significance to the field of additive manufacturing. In this study, we collected video data of different structural devices prepared by self-made photoresist materials under different laser parameters, and used a variety of convolutional neural network variant models to train and verify our collected datasets. The results show that the variant deep learning neural network model can classify the quality of polymer structures in milliseconds, and the test accuracy can reach 95%.

Citation Download Citation

Lijun Men, Ningning Hu, Yucheng Deng, Wenjun Zhang, and Ruixue Yin "Automatic quality monitoring of two-photon printed devices based on deep learning", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127094B (19 October 2023); https://doi.org/10.1117/12.2684914

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Video

Printing

Data modeling

Polymers

3D modeling

Education and training

Deep learning

Show All Keywords

Keywords/Phrases

Search In:

Publication Years