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Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking
Three-dimensional (3D) zigzag-line welding seams are found extensively in the manufacturing of marine engineering equipment, heavy lifting equipment, and logistics transportation equipment. Currently, due to the large amount of calculation and poor real-time performance of 3D welding seam detection...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7827984/ https://www.ncbi.nlm.nih.gov/pubmed/33430406 http://dx.doi.org/10.3390/s21020375 |
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author | Hong, Bo Jia, Aiting Hong, Yuxiang Li, Xiangwen Gao, Jiapeng Qu, Yuanyuan |
author_facet | Hong, Bo Jia, Aiting Hong, Yuxiang Li, Xiangwen Gao, Jiapeng Qu, Yuanyuan |
author_sort | Hong, Bo |
collection | PubMed |
description | Three-dimensional (3D) zigzag-line welding seams are found extensively in the manufacturing of marine engineering equipment, heavy lifting equipment, and logistics transportation equipment. Currently, due to the large amount of calculation and poor real-time performance of 3D welding seam detection algorithms, real-time tracking of 3D zigzag-line welding seams is still a challenge especially in high-speed welding. For the abovementioned problems, we proposed a method for the extraction of the pose information of 3D zigzag-line welding seams based on laser displacement sensing and density-based clustering point cloud segmentation during robotic welding. after thee point cloud data of the 3D zigzag-line welding seams was obtained online by the laser displacement sensor, it was segmented using theρ-Approximate DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. In the experiment, high-speed welding was performed on typical low-carbon steel 3D zigzag-line welding seams using gas metal arc welding. The results showed that when the welding velocity was 1000 mm/min, the proposed method obtained a welding seam position detection error of less than 0.35 mm, a welding seam attitude estimation error of less than two degrees, and the running time of the main algorithm was within 120 ms. Thus, the online extraction of the pose information of 3D zigzag-line welding seams was achieved and the requirements of welding seam tracking were met. |
format | Online Article Text |
id | pubmed-7827984 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-78279842021-01-25 Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking Hong, Bo Jia, Aiting Hong, Yuxiang Li, Xiangwen Gao, Jiapeng Qu, Yuanyuan Sensors (Basel) Article Three-dimensional (3D) zigzag-line welding seams are found extensively in the manufacturing of marine engineering equipment, heavy lifting equipment, and logistics transportation equipment. Currently, due to the large amount of calculation and poor real-time performance of 3D welding seam detection algorithms, real-time tracking of 3D zigzag-line welding seams is still a challenge especially in high-speed welding. For the abovementioned problems, we proposed a method for the extraction of the pose information of 3D zigzag-line welding seams based on laser displacement sensing and density-based clustering point cloud segmentation during robotic welding. after thee point cloud data of the 3D zigzag-line welding seams was obtained online by the laser displacement sensor, it was segmented using theρ-Approximate DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. In the experiment, high-speed welding was performed on typical low-carbon steel 3D zigzag-line welding seams using gas metal arc welding. The results showed that when the welding velocity was 1000 mm/min, the proposed method obtained a welding seam position detection error of less than 0.35 mm, a welding seam attitude estimation error of less than two degrees, and the running time of the main algorithm was within 120 ms. Thus, the online extraction of the pose information of 3D zigzag-line welding seams was achieved and the requirements of welding seam tracking were met. MDPI 2021-01-07 /pmc/articles/PMC7827984/ /pubmed/33430406 http://dx.doi.org/10.3390/s21020375 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hong, Bo Jia, Aiting Hong, Yuxiang Li, Xiangwen Gao, Jiapeng Qu, Yuanyuan Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking |
title | Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking |
title_full | Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking |
title_fullStr | Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking |
title_full_unstemmed | Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking |
title_short | Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking |
title_sort | online extraction of pose information of 3d zigzag-line welding seams for welding seam tracking |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7827984/ https://www.ncbi.nlm.nih.gov/pubmed/33430406 http://dx.doi.org/10.3390/s21020375 |
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