Abstract
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.
Highlights
China’s iron and steel industry has made tremendous contributions to the development of its national economy
Visual detection technology based on image processing has been widely used in various fields, such as medicine [1], the iron and steel industry [2,3], art [4], the textile industry [5], and the automobile industry [6] for its unique advantages of intuition, accuracy, and convenience
Detection methods are divided into the categories of statistics, filtering, models, and machine learning according to basic theories of image processing
Summary
China’s iron and steel industry has made tremendous contributions to the development of its national economy. Visual detection technology based on image processing has been widely used in various fields, such as medicine [1], the iron and steel industry [2,3], art [4], the textile industry [5], and the automobile industry [6] for its unique advantages of intuition, accuracy, and convenience. Detection methods for steel defects are classified as contact detection and non-contact detection [7]. The former receives information through direct contact with the sample surface by the sensing element of a contact-detection device. The latter is based on the technology of photoelectricity, and electromagnetism to obtain the parameter information of the sample surface without contacting it
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