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  2. 合肥物质科学研究院
  3. 中国科学院合肥物质科学研究院
  4. 中科院合肥物质科学研究院先进制造技术研究所
Image edge detection based tool condition monitoring with morphological component analysis

文献类型：期刊论文

作者Yu, Xiaolong1,2; Lin, Xin1,2; Dai, Yiquan2; Zhu, Kunpeng2,3
刊名ISA TRANSACTIONS
出版日期2017-07-01
卷号69页码:315-322
关键词Tool Condition Monitoring Image Edge Detection Morphological Component Analysis
DOI10.1016/j.isatra.2017.03.024
文献子类Article
英文摘要The measurement and monitoring of tool condition are keys to the product precision in the automated manufacturing. To meet the need, this study proposes a novel tool wear monitoring approach based on the monitored image edge detection. Image edge detection has been a fundamental tool to obtain features of images. This approach extracts the tool edge with morphological component analysis. Through the decomposition of original tool wear image, the approach reduces the influence of texture and noise for edge measurement. Based on the target image sparse representation and edge detection, the approach could accurately extract the tool wear edge with continuous and complete contour, and is convenient in charactering tool conditions. Compared to the celebrated algorithms developed in the literature, this approach improves the integrity and connectivity of edges, and the results have shown that it achieves better geometry accuracy and lower error rate in the estimation of tool conditions. (C) 2017 ISA. Published by Elsevier Ltd. All rights reserved.
WOS关键词FLANK WEAR MEASUREMENT ; SPARSE REPRESENTATION ; COMPUTER VISION ; MACHINE VISION ; NEURAL-NETWORK ; CLASSIFICATION ; ACCURACY
WOS研究方向Automation & Control Systems ; Engineering ; Instruments & Instrumentation
语种英语
WOS记录号WOS:000404826000028
资助机构CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; CAS 100 Talents Program ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; National Natural Science Foundation of China(51475443) ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/33448]  
专题合肥物质科学研究院_中科院合肥物质科学研究院先进制造技术研究所
作者单位1.Univ Sci & Technol China, Dept Automat, Hefei 230026, Peoples R China
2.Chinese Acad Sci, Hefei Inst Phys Sci, Inst Adv Mfg Technol, Huihong Bldg,Changwu Middle Rd 801, Changzhou 213164, Jiangsu, Peoples R China
3.Wuhan Univ Technol, Sch Logist Engn, Heping Rd 1178, Wuhan 430063, Hubei, Peoples R China
推荐引用方式
GB/T 7714		 Yu, Xiaolong,Lin, Xin,Dai, Yiquan,et al. Image edge detection based tool condition monitoring with morphological component analysis[J]. ISA TRANSACTIONS,2017,69:315-322.
APA Yu, Xiaolong,Lin, Xin,Dai, Yiquan,&Zhu, Kunpeng.(2017).Image edge detection based tool condition monitoring with morphological component analysis.ISA TRANSACTIONS,69,315-322.
MLA Yu, Xiaolong,et al."Image edge detection based tool condition monitoring with morphological component analysis".ISA TRANSACTIONS 69(2017):315-322.

入库方式： OAI收割

来源：合肥物质科学研究院

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