中文版 | English
Title

Analytical grinding force prediction with random abrasive grains of grinding wheels

Author
Corresponding AuthorZhang,Liangchi
Publication Years
2023-07-15
DOI
Source Title
ISSN
0020-7403
EISSN
1879-2162
Volume250
Abstract
A reliable prediction of grinding forces and surface morphology is critically important to the design of a grinding process. However, due to the complex microstructure of a grinding wheel which contains randomly-sized and randomly-distributed abrasive grains, a practical prediction model has been unavailable. This paper aims to develop a novel stochastic model to take into account the random nature of the abrasive grain size and their distribution in a grinding wheel, and hence to predict grinding forces more accurately. In addition, the evolution of the ground surface morphology, the real-time undeformed chip thickness, the interactions between the abrasive grains and the grain-workpiece contact mechanics are integrated into the modelling. Nanoindentation and tribology experiments were conducted to determine the micromechanical properties of the workpiece and abrasive grain. Grinding experiments were then performed to validate the predictions of the model. It was found, both theoretically and experimentally, that the stochastic model thus established can reliably predict grinding forces. It was also demonstrated that the proposed model can be effectively used to reveal the underlying mechanisms of grinding processes.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Corresponding
Funding Project
National Natural Science Foundation of China[52293401] ; Shenzhen Key Laboratory of Cross-scale Manufacturing Mechanics[ZDSYS20200810171201007]
WOS Research Area
Engineering ; Mechanics
WOS Subject
Engineering, Mechanical ; Mechanics
WOS Accession No
WOS:000955924100001
Publisher
ESI Research Field
ENGINEERING
Scopus EID
2-s2.0-85150059964
Data Source
Scopus
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/515711
DepartmentInstitute for Manufacturing Innovation
工学院_力学与航空航天工程系
Affiliation
1.Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology,School of Optics and Photonics,Beijing Institute of Technology,Beijing,100081,China
2.MIIT Key Laboratory of Complex-Field Intelligent Exploration,Beijing Institute of Technology,Beijing,100081,China
3.Shenzhen Key Laboratory of Cross-scale Manufacturing Mechanics,Southern University of Science and Technology,Shenzhen,Guangdong,518055,China
4.SUSTech Institute for Manufacturing Innovation,Southern University of Science and Technology,Shenzhen,Guangdong,518055,China
5.Department of Mechanics and Aerospace Engineering,Southern University of Science and Technology,Shenzhen,Guangdong,518055,China
Corresponding Author AffilicationSouthern University of Science and Technology;  Institute for Manufacturing Innovation;  Department of Mechanics and Aerospace Engineering
Recommended Citation
GB/T 7714
Wu,Zhonghuai,Zhang,Liangchi. Analytical grinding force prediction with random abrasive grains of grinding wheels[J]. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES,2023,250.
APA
Wu,Zhonghuai,&Zhang,Liangchi.(2023).Analytical grinding force prediction with random abrasive grains of grinding wheels.INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES,250.
MLA
Wu,Zhonghuai,et al."Analytical grinding force prediction with random abrasive grains of grinding wheels".INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES 250(2023).
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