Manufacturing Technology 2023, 23(5):691-699 | DOI: 10.21062/mft.2023.100

Surface Defect Detection Method for Welding Robot Workpiece Based on Machine Vision Technology

Yun Shi ORCID..., Yan-yan Zhu ORCID..., Jun-qi Wang ORCID...
West Anhui University, Luan, China

With the development of welding technology and the improvement of automation level, welding robots are playing an increasingly important role in industrial production. However, during the welding process, due to factors such as material characteristics, welding parameters, or improper processes, defects may appear on the surface of the workpiece, which may reduce the quality and service life of the workpiece. In order to solve this problem, this article used frequency domain feature extraction and nearest neighbor classifier in workpiece detection algorithms under machine vision technology to extract and classify surface defect images of workpiece, and studied the detection method of welding robot workpiece surface defects. The research results indicated that, under the same other conditions, the accuracy of machine vision technology was over 90% for all five different defect types, while the accuracy of traditional technology was between 75.5% and 84%. The performance of machine vision technology was far superior to traditional technology, indicating that machine vision technology could improve the accuracy of welding robot workpiece surface defect detection methods.

Keywords: Surface defect detection of workpiece, Machine vision technology, Welding robot, Accuracy rate, Detection and response time
Grants and funding:

This research was supported by the School-level Research Projects of West Anhui University (WXZR202211), West Anhui University high-level Personnel Research Funding Project (WGKQ2022015, WGKQ2021067), Anhui Provincial Quality Engineering Project (2021sysxzx031, 2022sx171), School level Quality Engineering Project of West Anhui University (wxxy2022085), the Open Fund of Anhui Undergrowth Crop Intelligent Equipment Engineering Research Center (AUCIEERC-2022-05), Key Project of Natural Science Research of Anhui Provincial Department of Education (KJ2021A0946)

Received: August 22, 2023; Revised: November 27, 2023; Accepted: November 30, 2023; Published: December 6, 2023  Show citation

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Shi Y, Zhu Y, Wang J. Surface Defect Detection Method for Welding Robot Workpiece Based on Machine Vision Technology. Manufacturing Technology. 2023;23(5):691-699. doi: 10.21062/mft.2023.100.
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