Article(id=1274058242851365748, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1274058225780560684, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1753891200000, receivedDateStr=2025-07-31, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1781688755952, onlineDateStr=2026-06-17, pubDate=1777046400000, pubDateStr=2026-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1781688755952, onlineIssueDateStr=2026-06-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1781688755952, creator=13701087609, updateTime=1781688755952, updator=13701087609, issue=Issue{id=1274058225780560684, tenantId=1146029695717560320, journalId=1185652524569653253, year='2026', volume='52', issue='2', pageStart='1', pageEnd='98', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1781688751881, creator=13701087609, updateTime=1781688793534, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1274058400561389755, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1274058225780560684, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1274058400561389756, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1274058225780560684, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=18, endPage=21, ext={EN=ArticleExt(id=1274058244067713910, articleId=1274058242851365748, tenantId=1146029695717560320, journalId=1185652524569653253, language=EN, title=Research Progress on Detection Technologies for Surface Defects of Steel, columnId=1187100781414069182, journalTitle=Science & Technology of Baotou Steel, columnName=Production Practices and Management, runingTitle=null, highlight=null, articleAbstract=

The steel is the core in modern industrial system and its surface quality influences performances and service life of products. In this paper, it is focused on the research on detection technologies for surface defects of steel, systematically introduced common types of surface defects and their formation mechanisms, comprehensively analyzed advantages and disadvantages of traditional detection methods, elaborated the principles, application results and challenges facing of emerging detection technologies represented by machine vision and deep learning as well as deeply discussed the defect repair technologies and surface quality control strategies. The research showed that the detection precision and efficiency were significantly improved with the emerging detection technologies, but they need to be improved from such aspects as adaptability in complicated industrial environment. In the future, the detection technologies for surface defects of steel will be developed towards the directions of multi-technology fusion, intelligence and standardization to meet the increasing industrial production requirements.

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钢材在现代工业体系中占据核心地位，其表面质量影响产品性能与使用寿命。文章聚焦钢材表面缺陷检测技术研究，系统梳理了常见的表面缺陷类型及其形成机制。全面剖析了传统检测方法的优劣势，阐述了以机器视觉和深度学习为代表的新兴检测技术原理、应用成果及面临的挑战，深入探讨了缺陷修复技术及表面质量控制策略。研究表明，新兴检测技术显著提升了检测精度与效率，但在复杂工业环境下的适应性等方面仍需完善。未来，钢材表面缺陷检测技术将朝着多技术融合、智能化、标准化方向发展，以满足不断提升的工业生产需求。

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张晓晨（1996-），女，内蒙古乌兰察布市人，硕士，助理工程师，现从事特钢产品研发工作。

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张晓晨（1996-），女，内蒙古乌兰察布市人，硕士，助理工程师，现从事特钢产品研发工作。

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