Research on steel surface defect detection system based on YOLOv5s-SE-CA model and BEMD image enhancement-Reference-Cited by-同舟云学术

Research on steel surface defect detection system based on YOLOv5s-SE-CA model and BEMD image enhancement

Published:2024-08-25 Issue: Volume: Page:1-20
ISSN:1058-9759
Container-title:Nondestructive Testing and Evaluation
language:en
Short-container-title:Nondestructive Testing and Evaluation

Author:

Wang Shan¹²,Fan Xueke¹²,Zhao Ziye¹²,Qiao Zijian³,Wang Na⁴,Qiu Yuhang¹²,Jia Xiaoyu¹²

Affiliation:

1. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin, China

2. National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology, Tianjin, China

3. School of Mechanical Engineering and Mechanics, Ningbo University, Ningbo, China

4. Research and Development Department, Tianjin Wuyue Aviation Technology Co. Ltd, Tianjin, China

Funder

Tianjin Natural Science Foundation Youth Project

Natural Science Basic Research Plan in Shaanxi Province of China

Gansu Provincial Department of Education: Innovation Fund Project for University Teachers

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10589759.2024.2393205

Reference46 articles.

1. Surface defect detection of steel strips based on classification priority YOLOv3-dense network

2. Noise-boosted weak signal detection in fractional nonlinear systems enhanced by increasing potential-well width and its application to mechanical fault diagnosis

3. Production of hydrogen and carbon in the petrochemical industry by cracking of hydrocarbons in the process of heat utilization in steel production

4. Lock-in inductive thermography for surface crack detection in different metals

5. An adaptive sensor placement algorithm for structural health monitoring based on multi-objective iterative optimization using weight factor updating