TY - JOUR
T1 - Milling force modeling of worn tool and tool flank wear recognition in end milling
AU - Hou, Yongfeng
AU - Zhang, Dinghua
AU - Wu, Baohai
AU - Luo, Ming
N1 - Publisher Copyright:
© 1996-2012 IEEE.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - The wear state of a cutting tool is an important factor which affects machining quality. Therefore, monitoring tool wear is extremely essential to ensure workpiece quality and improve tool life. This paper models the milling forces of a worn tool and proposes a recognition method of milling tool wear state based on the influence relationships between the milling force features and tool wear. In the milling force model, the friction effect force and the shearing force are treated separately, and the friction stress distribution on tool flank is described. Then the force model is calibrated and verified through experiments. In the tool wear recognition method, the relationship between the milling force feature vector and tool wear is investigated. On this basis, the tool flank wear recognition method is proposed. A tool wear experiment is performed using superalloy material. In the experiment, the recognition results are expressed in confidence intervals which can represent the recognized tool wear more effectively and accurately. Finally, the scheme of tool flank wear online monitoring is proposed.
AB - The wear state of a cutting tool is an important factor which affects machining quality. Therefore, monitoring tool wear is extremely essential to ensure workpiece quality and improve tool life. This paper models the milling forces of a worn tool and proposes a recognition method of milling tool wear state based on the influence relationships between the milling force features and tool wear. In the milling force model, the friction effect force and the shearing force are treated separately, and the friction stress distribution on tool flank is described. Then the force model is calibrated and verified through experiments. In the tool wear recognition method, the relationship between the milling force feature vector and tool wear is investigated. On this basis, the tool flank wear recognition method is proposed. A tool wear experiment is performed using superalloy material. In the experiment, the recognition results are expressed in confidence intervals which can represent the recognized tool wear more effectively and accurately. Finally, the scheme of tool flank wear online monitoring is proposed.
KW - Friction effect force
KW - Milling force feature vector
KW - Milling force modeling
KW - Model calibration
KW - Tool wear recognition
UR - http://www.scopus.com/inward/record.url?scp=85028215774&partnerID=8YFLogxK
U2 - 10.1109/TMECH.2014.2363166
DO - 10.1109/TMECH.2014.2363166
M3 - 文章
AN - SCOPUS:85028215774
SN - 1083-4435
VL - 20
SP - 1024
EP - 1035
JO - IEEE/ASME Transactions on Mechatronics
JF - IEEE/ASME Transactions on Mechatronics
IS - 3
M1 - 6965588
ER -