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Zhendong He, Wenbin Yang, Yanjie Liu, Anping Zheng, Jie Liu, Taishan Lou and Jie Zhang
Ensuring the safety of transmission lines necessitates effective insulator defect detection. Traditional methods often need more efficiency and accuracy, particularly for tiny defects. This paper proposes an innovative insulator defect recognition method...
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Baobao Liu, Heying Wang, Zifan Cao, Yu Wang, Lu Tao, Jingjing Yang and Kaibing Zhang
Defect detection holds significant importance in improving the overall quality of fabric manufacturing. To improve the effectiveness and accuracy of fabric defect detection, we propose the PRC-Light YOLO model for fabric defect detection and establish a ...
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Shancheng Tang, Ying Zhang, Zicheng Jin, Jianhui Lu, Heng Li and Jiqing Yang
The number of defect samples on the surface of aluminum profiles is small, and the distribution of abnormal visual features is dispersed, such that the existing supervised detection methods cannot effectively detect undefined defects. At the same time, t...
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Haotao Wang, Haijun Zhang, Ming Zhou, Chengbo Gu, Sutong Bai and Hao Lin
SiCp/Al composites are used in the aerospace, automotive, and electronics fields, among others, due to their excellent physical and mechanical properties. However, as they are hard-to-machine materials, poor surface quality has become a major limitation ...
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Zhihang Liu, Pengfei He and Feifei Wang
Image super-resolution reconstruction technology can boost image resolution and aid in the discovery of PCB flaws. The traditional SRGAN algorithm produces reconstructed images with great realism, but it also has the disadvantages of insufficient feature...
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Qinnan Fei, Jiancheng Cao, Wanli Xu, Linzhao Jiang, Jun Zhang, Hui Ding, Xiaohong Li and Jingli Yan
This study concentrates on the field of intelligent nondestructive testing, presenting a CNN?based method for accurately evaluating the depth of micro?defects on or near a surface. The innovation in this study lies in several key aspects: (1) The establi...
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Yifan Qi, Yongming Li and Anyu Du
Insulators are widely used in various aspects of the power system and play a crucial role in ensuring the safety and stability of power transmission. Insulator detection is an important measure to guarantee the safety and stability of the transmission sy...
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Xulong Yu, Qiancheng Yu, Qunyue Mu, Zhiyong Hu and Jincai Xie
Traditional manual visual detection methods are inefficient, subjective, and costly, making them prone to false and missed detections. Deep-learning-based defect detection identifies the types of defects and pinpoints their locations. By employing this a...
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Yongkang Wang, Jundong Zhang, Jinting Zhu, Yuequn Ge and Guanyu Zhai
In the intelligent engine room, the visual perception of ship engine room equipment is the premise of defect identification and the replacement of manual operation. This paper improves YOLOv5 for the problems of mutual occlusion of cabin equipment, an un...
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Xinbo Huang, Zhiwei Song, Chao Ji, Ye Zhang and Luya Yang
Different types of surface defects will occur during the production of strip steel. To ensure production quality, it is essential to classify these defects. Our research indicates that two main problems exist in the existing strip steel surface defect cl...
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