Research on Weld Seam Marking Based on Machine Vision Technology

The rapid development of machine vision technology has made it widely used in various industrial fields. The detection of welding quality can also be achieved through this technology. The core of welding quality inspection is to realize the marking of weld features. To solve the problem of weld feature marking, the GUI weld marking interface is built based on MATLAB. After the process of image acquisition, image preprocessing, edge detection and feature extraction, the weld marking experiment of is finally completed. Based on data analysis of the experiment, it can be concluded that Canny edge detection operator has the best marking effect and the most stable detection for the research object used.

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Publication Details

Journal
Academic Journal of Science and Technology
Published
2024-09-14
DOI
https://doi.org/10.54097/1pc4y902
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
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article

Research on Weld Seam Marking Based on Machine Vision Technology

Qian Fu, Shunyang Hu, Chenlei Zhao
Academic Journal of Science and Technology
Industrial Vision Systems and Defect Detection
article

Research on Weld Seam Marking Based on Machine Vision Technology

Qian Fu, Shunyang Hu, Chenlei Zhao
article en

Abstract

The rapid development of machine vision technology has made it widely used in various industrial fields. The detection of welding quality can also be achieved through this technology. The core of welding quality inspection is to realize the marking of weld features. To solve the problem of weld feature marking, the GUI weld marking interface is built based on MATLAB. After the process of image acquisition, image preprocessing, edge detection and feature extraction, the weld marking experiment of is finally completed. Based on data analysis of the experiment, it can be concluded that Canny edge detection operator has the best marking effect and the most stable detection for the research object used.

Academic Journal of Science and TechnologyVol. 12(2)
Geely (China) (CN)
Openalex Percentile: Top 78%
Industrial Vision Systems and Defect Detection
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