Research Progress of Visual Inspection Technology of Steel Products—A Review

• Main Authors: Xiaohong Sun, Jinan Gu, Shixi Tang, Jing Li
• Format: Article
• Language: English
• Published: MDPI AG 2018-11-01
• Series: Applied Sciences
• Subjects: defect inspection; image processing; feature extraction; classification methods
• Online Access: https://www.mdpi.com/2076-3417/8/11/2195

The automation and intellectualization of the manufacturing processes in the iron and steel industry needs the strong support of inspection technologies, which play an important role in the field of quality control. At present, visual inspection technology based on image processing has an absolute advantage because of its intuitive nature, convenience, and efficiency. A major breakthrough in this field can be achieved if sufficient research regarding visual inspection technologies is undertaken. Therefore, the purpose of this article is to study the latest developments in steel inspection relating to the detected object, system hardware, and system software, existing problems of current inspection technologies, and future research directions. The paper mainly focuses on the research status and trends of inspection technology. The network framework based on deep learning provides space for the development of end-to-end mode inspection technology, which would greatly promote the implementation of intelligent manufacturing.