TY - JOUR
T1 - Identification of cutting force coefficients in machining process considering cutter vibration
AU - Yao, Qi
AU - Luo, Ming
AU - Zhang, Dinghua
AU - Wu, Baohai
N1 - Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2018/3/15
Y1 - 2018/3/15
N2 - Among current cutting force models, cutting force coefficients still are the foundation of predicting calculation combined with consideration of geometry engagement variation, equipment characteristics, material properties and so on. Attached with unimpeachable significance, the traditional and some novel identification methods of cutting force coefficient are still faced with trouble, including repeated onerous work, over ideal measuring condition, variation of value due to material divergence, interference from measuring units. To utilize the large amount of data from real manufacturing section, enlarge data sources and enrich cutting data base for former prediction task, a novel identification method is proposed by considering stiffness properties of the cutter-holder-spindle system in this paper. According to previously proposed studies, the direct result of cutter vibration is the form of dynamic undeformed chip thickness. This fluctuation is considered in two stages of this investigation. Firstly, a cutting force model combined with cutter vibration is established in detailed way. Then, on the foundation of modeling, a novel identification method is developed, in which the dynamic undeformed chip thickness could be obtained by using collected data. In a carefully designed experiment procedure, the reliability of model is validated by comparing predicted and measured results. Under different cutting condition and cutter stiffness, data is collected for the justification of identification method. The results showed divergence in calculated coefficients is acceptable confirming the possibility of accomplishing targets by applying this new method. In discussion, the potential directions of improvement are proposed.
AB - Among current cutting force models, cutting force coefficients still are the foundation of predicting calculation combined with consideration of geometry engagement variation, equipment characteristics, material properties and so on. Attached with unimpeachable significance, the traditional and some novel identification methods of cutting force coefficient are still faced with trouble, including repeated onerous work, over ideal measuring condition, variation of value due to material divergence, interference from measuring units. To utilize the large amount of data from real manufacturing section, enlarge data sources and enrich cutting data base for former prediction task, a novel identification method is proposed by considering stiffness properties of the cutter-holder-spindle system in this paper. According to previously proposed studies, the direct result of cutter vibration is the form of dynamic undeformed chip thickness. This fluctuation is considered in two stages of this investigation. Firstly, a cutting force model combined with cutter vibration is established in detailed way. Then, on the foundation of modeling, a novel identification method is developed, in which the dynamic undeformed chip thickness could be obtained by using collected data. In a carefully designed experiment procedure, the reliability of model is validated by comparing predicted and measured results. Under different cutting condition and cutter stiffness, data is collected for the justification of identification method. The results showed divergence in calculated coefficients is acceptable confirming the possibility of accomplishing targets by applying this new method. In discussion, the potential directions of improvement are proposed.
KW - Chip thickness
KW - Cutting force
KW - Cutting force coefficient
KW - Machining
KW - Milling process
UR - http://www.scopus.com/inward/record.url?scp=85033575851&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2017.09.038
DO - 10.1016/j.ymssp.2017.09.038
M3 - 文章
AN - SCOPUS:85033575851
SN - 0888-3270
VL - 103
SP - 39
EP - 59
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
ER -