title: Image edge detection based tool condition monitoring with morphological component analysis.
abstract: 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.
authors.affiliation: Department of Automation, University of Science and Technology of China, Hefei 230026, China; Institute of Advanced Manufacturing Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Huihong Building, Changwu Middle Road 801, Changzhou 213164, Jiangsu, China.
authors.forename: Xiaolong
authors.initials: X
authors.lastname: Yu
authors.affiliation: Department of Automation, University of Science and Technology of China, Hefei 230026, China; Institute of Advanced Manufacturing Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Huihong Building, Changwu Middle Road 801, Changzhou 213164, Jiangsu, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Lin
authors.affiliation: Institute of Advanced Manufacturing Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Huihong Building, Changwu Middle Road 801, Changzhou 213164, Jiangsu, China.
authors.forename: Yiquan
authors.initials: Y
authors.lastname: Dai
authors.affiliation: Institute of Advanced Manufacturing Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Huihong Building, Changwu Middle Road 801, Changzhou 213164, Jiangsu, China; School of Logistics Engineering, Wuhan University of Technology, Heping Road 1178#, Wuhan, 430063 Hubei, China.. Electronic address: zhukp@iamt.ac.cn.
authors.forename: Kunpeng
authors.initials: K
authors.lastname: Zhu
keywords: Image edge detection; Morphological component analysis; Tool condition monitoring