TY - GEN
T1 - An on-line tool wear monitoring method based on cutting power
AU - Wan, Teng
AU - Chen, Xingzheng
AU - Li, Congbo
AU - Tang, Ying
N1 - Funding Information:
* Manuscript received March 18, 2018. This work was supported by the National Natural Science Foundation of China (No.51475059). 1 The first two authors made equal contribution to this work.
PY - 2018/12/4
Y1 - 2018/12/4
N2 - In a CNC batch process, excessive tool wear will lead to a bad surface quality of the final product. On-line tool wear monitoring is recognized as an effective method to reduce the impact of the tool wear on surface quality. In this paper, a cutting power model is firstly established with the consideration of tool wear and cutting parameters. A novel on-line tool wear monitoring approach for CNC batch processing is then proposed and a monitoring system is developed. Result of the case study shows that the proposed approach is effective in tool wear on-line monitoring.
AB - In a CNC batch process, excessive tool wear will lead to a bad surface quality of the final product. On-line tool wear monitoring is recognized as an effective method to reduce the impact of the tool wear on surface quality. In this paper, a cutting power model is firstly established with the consideration of tool wear and cutting parameters. A novel on-line tool wear monitoring approach for CNC batch processing is then proposed and a monitoring system is developed. Result of the case study shows that the proposed approach is effective in tool wear on-line monitoring.
UR - http://www.scopus.com/inward/record.url?scp=85059990027&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059990027&partnerID=8YFLogxK
U2 - 10.1109/COASE.2018.8560412
DO - 10.1109/COASE.2018.8560412
M3 - Conference contribution
AN - SCOPUS:85059990027
T3 - IEEE International Conference on Automation Science and Engineering
SP - 205
EP - 210
BT - 2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018
PB - IEEE Computer Society
T2 - 14th IEEE International Conference on Automation Science and Engineering, CASE 2018
Y2 - 20 August 2018 through 24 August 2018
ER -