Micro-milling tool wear monitoring under variable cutting parameters and runout using fast cutting force coefficient identification method

doi:10.1007/s00170-020-06272-z

	Micro-milling tool wear monitoring under variable cutting parameters and runout using fast cutting force coefficient identification method
	Liu, Tongshun 2; Zhu, Kunpeng 1; Wang, Gang 2
刊名	INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
	2020-11-07
关键词	Micro-milling Cutting force model Tool runout Cutting force coefficient identification Tool wear monitoring
ISSN号	0268-3768
DOI	10.1007/s00170-020-06272-z
通讯作者	Liu, Tongshun(tongshunliu@hotmail.com)
英文摘要	Extracting discriminative tool wear features is of great importance for tool wear monitoring in micro-milling. However, due to the dependency on tool runout and cutting parameters, the traditional tool wear features are incompetent to monitor the tool wear condition in micro-milling with significant tool runout and varied cutting parameter interactions. In this study, micro-milling cutting force is represented by a parametric model including variable cutting parameters, tool runout, and tool wear. The cutting force coefficient in the model, which is not only discriminative to the tool wear condition but also independent to the tool runout and cutting parameters, is extracted as the micro-milling tool wear feature. To reduce the computation cost, a fast neural network-based method is proposed to identify the tool runout and the cutting force coefficient from the cutting force signal. Experimental results show that the proposed cutting force coefficient-based approach is efficient to monitor the micro-milling tool wear under varied cutting parameters and tool runout.
资助项目	Natural Science Foundation of the Jiangsu Higher Education Institutions of China[19KJB460007] ; National Natural Science Foundation of China[51805341] ; Natural Science Foundation of Jiangsu Province[BK20180843]
WOS关键词	CHIP THICKNESS MODEL ; LIFE PREDICTION ; NEURAL-NETWORK ; SYSTEM ; STATE ; SENSOR
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	SPRINGER LONDON LTD
WOS记录号	WOS:000587273600004
资助机构	Natural Science Foundation of the Jiangsu Higher Education Institutions of China ; National Natural Science Foundation of China ; Natural Science Foundation of Jiangsu Province
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/105160]
专题	中国科学院合肥物质科学研究院
通讯作者	Liu, Tongshun
作者单位	1.Chinese Acad Sci, Inst Adv Mfg Technol, Hefei Inst Phys Sci, Changzhou 213164, Jiangsu, Peoples R China 2.Soochow Univ, Sch Mech & Elect Engn, Suzhou 215021, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Liu, Tongshun,Zhu, Kunpeng,Wang, Gang. Micro-milling tool wear monitoring under variable cutting parameters and runout using fast cutting force coefficient identification method[J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,2020.
APA	Liu, Tongshun,Zhu, Kunpeng,&Wang, Gang.(2020).Micro-milling tool wear monitoring under variable cutting parameters and runout using fast cutting force coefficient identification method.INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY.
MLA	Liu, Tongshun,et al."Micro-milling tool wear monitoring under variable cutting parameters and runout using fast cutting force coefficient identification method".INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2020).