Exploration of Laser Marking Path and Algorithm Based on Intelligent Computing and Internet of Things.


Journal

Computational intelligence and neuroscience
ISSN: 1687-5273
Titre abrégé: Comput Intell Neurosci
Pays: United States
ID NLM: 101279357

Informations de publication

Date de publication:
2022
Historique:
received: 28 04 2022
accepted: 31 05 2022
entrez: 5 7 2022
pubmed: 6 7 2022
medline: 6 7 2022
Statut: epublish

Résumé

Nowadays, laser processing technology is being used more and more in various fields, and the requirements for laser control procedures are getting higher and higher. This paper aims to study the path generation problem of laser marking technology in order to improve the efficiency of laser marking as well as the protection of the marking material. Therefore, we creatively propose two-path generation methods, namely, sawtooth parallel and contour parallel, and design the boundary curve offset algorithm and domain partition intersection algorithm for the computer simulation of the two marking paths, respectively. Through the simulation, we discussed the efficiency and marking quality of the two path generation methods and gave the conclusion that the efficiency of the sawtooth parallel path generation method is greater than that of the contour parallel path generation method under specific parameters.

Identifiants

pubmed: 35785097
doi: 10.1155/2022/7443410
pmc: PMC9249445
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

7443410

Informations de copyright

Copyright © 2022 Gang Lu et al.

Déclaration de conflit d'intérêts

The authors declare that there are no conflicts of interest.

Références

Opt Lett. 1994 Jan 1;19(1):55-7
pubmed: 19829541

Auteurs

Gang Lu (G)

Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan, Shandong, China.

Yide Liu (Y)

Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan, Shandong, China.

Xue Yao (X)

Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan, Shandong, China.

Jiachen Yang (J)

Swinburne College, Shandong University of Science and Technology, Jinan, Shandong, China.

Cheng Jia (C)

Swinburne College, Shandong University of Science and Technology, Jinan, Shandong, China.

Classifications MeSH