A detection and configuration method for welding completeness in the automotive body-in-white panel based on digital twin

被引：20

作者：

Li, Hao ^{[1
]}

Li, Bing ^{[1
]}

Liu, Gen ^{[1
]}

Wen, Xiaoyu ^{[1
]}

Wang, Haoqi ^{[1
]}

Wang, Xiaocong ^{[1
]}

Zhang, Shuai ^{[2
]}

Zhai, Zhongshang ^{[3
]}

Yang, Wenchao ^{[1
]}

机构：

[1] Zhengzhou Univ Light Ind, Key Lab Intelligent Mfg Mech Equipment, Zhengzhou 450002, Peoples R China

[2] Univ Greenwich, Pk Row, London SE10 9LS, England

[3] Tianjin Miracle Intelligent Equipment Co LTD, Tianjin 300131, Peoples R China

来源：

SCIENTIFIC REPORTS | 2022年 / 12卷 / 01期

基金：

中国国家自然科学基金;

关键词：

AUGMENTED REALITY;

D O I：

10.1038/s41598-022-11440-0

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

To address the problems of poor welding completeness and inefficient configuration for defective automotive body-in-white panels, we propose a method for detecting and configuring the welding completeness of automotive body-in-white panels based on digital twin (DT) and mixed reality (MR). The method uses DT to build an MR-oriented DT framework for the detections and configuration of body-in-white panel welding completeness. We propose a method to build a DT knowledge base for panels, a Yolov4-based welding completeness detection method, and a MR-based configuration method for the welding completeness in panels. Our team develop a panel welding completeness detection and configuration system to fully validate the effectiveness of the method.

引用

页数：11

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