AUTOMATIC DEFECT DETECTION IN THE PRINTING PROCESS OF FDM 3D PRINTERS USING NEURAL NETWORK TECHNOLOGY

The analysis of the features of various neural network programming technologies has been carried out in order to identify the most suitable for detecting defects in time FDM 3D printing by analyzing images from the builtin 3D printer camera. A technique for detecting the most common defects and an integrated system for its implementation, including a video camera, image analysis hardware and basic principles of neural network programming, are proposed.

Authors

Publication Details

Journal
IZVESTIA VOLGOGRAD STATE TECHNICAL UNIVERSITY
Published
2025-01-01
DOI
https://doi.org/10.35211/1990-5297-2025-1-296-57-62
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
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article

AUTOMATIC DEFECT DETECTION IN THE PRINTING PROCESS OF FDM 3D PRINTERS USING NEURAL NETWORK TECHNOLOGY

K. A. Drapak, Vadim Fomin, K.V. VAGANOV
IZVESTIA VOLGOGRAD STATE TECHNICAL UNIVERSITY
Industrial Vision Systems and Defect Detection
article

AUTOMATIC DEFECT DETECTION IN THE PRINTING PROCESS OF FDM 3D PRINTERS USING NEURAL NETWORK TECHNOLOGY

K. A. Drapak, Vadim Fomin, K.V. VAGANOV
article en

Abstract

The analysis of the features of various neural network programming technologies has been carried out in order to identify the most suitable for detecting defects in time FDM 3D printing by analyzing images from the builtin 3D printer camera. A technique for detecting the most common defects and an integrated system for its implementation, including a video camera, image analysis hardware and basic principles of neural network programming, are proposed.

IZVESTIA VOLGOGRAD STATE TECHNICAL UNIVERSITY(1 (296))
Openalex Percentile: Top 91%
Industrial Vision Systems and Defect Detection
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AUTOMATIC DEFECT DETECTION IN THE PRINTING PROCESS OF FDM 3D PRINTERS USING NEURAL NETWORK TECHNOLOGY — K. A. Drapak, Vadim Fomin, et al. · IZVESTIA VOLGOGRAD STATE TECHNICAL UNIVERSITY (2025) | TGRS Research Map | TGRS