Segmented Embedded Rapid Defect Detection Method for Bearing Surface Defects

doi:10.3390/machines9020040

	Segmented Embedded Rapid Defect Detection Method for Bearing Surface Defects
	Lei, Linjian1,2,3,4 ; Sun, Shengli 1,4; Zhang, Yue 1,2,4; Liu, Huikai 1,2,4; Xie, Hui 1,2,4
	2021-02
发表期刊	MACHINES (IF:2.1[JCR-2023],2.2[5-Year])
EISSN	2075-1702
卷号	9 期号:2 页码:#VALUE!
DOI	10.3390/machines9020040
摘要	The rapid development of machine vision has prompted the continuous emergence of new detection systems and algorithms in surface defect detection. However, most of the existing methods establish their systems with few comparisons and verifications, and the methods described still have various problems. Thus, an original defect detection method: Segmented Embedded Rapid Defect Detection Method for Surface Defects (SERDD) is proposed in this paper. This method realizes the two-way fusion of image processing and defect detection, which can efficiently and accurately detect surface defects such as depression, scratches, notches, oil, shallow characters, abnormal dimensions, etc. Besides, the character recognition method based on Spatial Pyramid Character Proportion Matching (SPCPM) is used to identify the engraved characters on the bearing dust cover. Moreover, the problem of characters being cut in coordinate transformation is solved through Image Self-Stitching-and-Cropping (ISSC). This paper adopts adequate real image data to verify and compare the methods and proves the effectiveness and advancement through detection accuracy, missing alarm rate, and false alarm rate. This method can provide machine vision technical support for bearing surface defect detection in its real sense.
关键词	bearing surface defect defect detection image processing character recognition
URL	查看原文
收录类别	SCI ; SCIE
语种	英语
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic ; Engineering, Mechanical
WOS记录号	WOS:000622684800001
出版者	MDPI
原始文献类型	Article
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/125837
专题	信息科学与技术学院_硕士生信息科学与技术学院_博士生
通讯作者	Sun, Shengli
作者单位	1.Chinese Acad Sci, Shanghai Inst Tech Phys, Shanghai 200083, Peoples R China; 2.Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing 100049, Peoples R China; 3.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China; 4.Chinese Acad Sci, Key Lab Intelligent Infrared Percept, Shanghai 200083, Peoples R China
第一作者单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Lei, Linjian,Sun, Shengli,Zhang, Yue,et al. Segmented Embedded Rapid Defect Detection Method for Bearing Surface Defects[J]. MACHINES,2021,9(2):#VALUE!.
APA	Lei, Linjian,Sun, Shengli,Zhang, Yue,Liu, Huikai,&Xie, Hui.(2021).Segmented Embedded Rapid Defect Detection Method for Bearing Surface Defects.MACHINES,9(2),#VALUE!.
MLA	Lei, Linjian,et al."Segmented Embedded Rapid Defect Detection Method for Bearing Surface Defects".MACHINES 9.2(2021):#VALUE!.