The prediction model and experimental research of grinding surface roughness based on AE signal

doi:10.1007/s00170-022-09135-x

CORC > 金属研究所 > 中国科学院金属研究所

	The prediction model and experimental research of grinding surface roughness based on AE signal
	Yin, Guoqiang 1; Wang, Jiahui 1; Guan, Yunyun 1; Wang, Dong 2; Sun, Yao 1
刊名	INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
	2022-04-16
页码	13
关键词	AE signal Multi-information fusion model Grinding process Surface roughness
ISSN号	0268-3768
DOI	10.1007/s00170-022-09135-x
通讯作者	Yin, Guoqiang(yinguoqiang@me.neu.edu.cn)
英文摘要	This paper is based on the investigation of the relationship between the processing parameters and the characteristic parameters of acoustic emission signal (AE signal) including RMS value, ringing count, and signal spectrum during the grinding of several difficult-to-machine metallic materials; the variation of AE signal characteristic parameters and spectrum with the parameters of grinding depth a(p), grinding wheel velocity v(s), and feed velocity v(w) was analyzed, then the corresponding relationship between acoustic emission signal characteristic parameters and machining surface roughness was given. On this basis, the multi-information fusion algorithm based on BP neural network was used to reasonably fuse various characteristic parameters of AE signals, then predict and recognize the surface roughness of grinding workpieces. Finally, the established model was optimized by using genetic algorithm, which significantly improved the prediction accuracy and provided a reliable prediction model for the grinding of difficult-to-machine alloys, providing a feasible method for predicting surface roughness for practical production.
资助项目	National Natural Science Foundation of China[51771193] ; National Natural Science Foundation of China[52005092] ; Fundamental Research Funds for the Central Universities[N2103013]
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	SPRINGER LONDON LTD
WOS记录号	WOS:000782874300002
资助机构	National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
内容类型	期刊论文
源URL	[http://ir.imr.ac.cn/handle/321006/172800]
专题	金属研究所_中国科学院金属研究所
通讯作者	Yin, Guoqiang
作者单位	1.Northeastern Univ, Sch Mech Engn & Automat, Shenyang 110819, Peoples R China 2.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, Shenyang 110016, Peoples R China
推荐引用方式 GB/T 7714	Yin, Guoqiang,Wang, Jiahui,Guan, Yunyun,et al. The prediction model and experimental research of grinding surface roughness based on AE signal[J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,2022:13.
APA	Yin, Guoqiang,Wang, Jiahui,Guan, Yunyun,Wang, Dong,&Sun, Yao.(2022).The prediction model and experimental research of grinding surface roughness based on AE signal.INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,13.
MLA	Yin, Guoqiang,et al."The prediction model and experimental research of grinding surface roughness based on AE signal".INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2022):13.