Back to Search Start Over

Face gear generating grinding residual model based on the normal cutting depth iterative method.

Authors :
Cai, Sijie
Cai, Zhiqin
Yao, Bin
Shen, Zhihuang
Liu, Jianchun
Huang, Haipeng
Lin, Bingjing
Lin, Jianchun
Huang, Haibin
Source :
International Journal of Advanced Manufacturing Technology; May2023, Vol. 126 Issue 1/2, p355-369, 15p
Publication Year :
2023

Abstract

The generating grinding method has the characteristics of high machining accuracy and high efficiency. Therefore, it is widely used in the finishing process of the face gear tooth surface. The physical performance of the grinding process is an important factor that influences the machining accuracy of the face gear tooth surface. Therefore, to improve the manufacturing accuracy of the face gear, it is necessary to accurately simulate the grinding process of the face gear. Owing to the influence of the complex spatial geometric characteristics of the face gear tooth surface and the grinding wheel, establishing a surface residual modeling method for the face gear is a key challenge in simulating the generating grinding process. To address the aforementioned issues, this study proposes a normal cutting depth iterative method to calculate the grinding residual in the face gear generating grinding process. This method considers the complex 3D spatial characteristics of the face gear tooth surface and establishes the spatial residual model of each node of the face gear surface in the process of generating grinding. Compared with other residual algorithms based on 2D truncation or Boolean operation of face gears, this algorithm has higher computational accuracy and efficiency. Thus, it lays the foundation for accurately establishing the complex spatial microscopic surface topography in the face gear generating grinding process. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
126
Issue :
1/2
Database :
Complementary Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
163121951
Full Text :
https://doi.org/10.1007/s00170-023-11121-w