Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5003946 | ISA Transactions | 2017 | 8 Pages |
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.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Xiaolong Yu, Xin Lin, Yiquan Dai, Kunpeng Zhu,