Search

Your search keyword '"Yao, Jiasheng"' showing total 8 results
Start Over Author "Yao, Jiasheng"
8 results on '"Yao, Jiasheng"'

1. Simulation of Nanoindentation Technology Based on Rough Surface

Author

Ye, Zihao, Wang, Yonghang, Yao, Jiasheng, Jiang, Jiankang, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Halgamuge, Saman K., editor, Zhang, Hao, editor, Zhao, Dingxuan, editor, and Bian, Yongming, editor

Published
2024
Full Text
View/download PDF

2. Interactively Mining Interesting Spatial Co-Location Patterns by Using Fuzzy Ontologies

Author

Yao, Jiasheng, Bao, Xuguang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yuan, Long, editor, Yang, Shiyu, editor, Li, Ruixuan, editor, Kanoulas, Evangelos, editor, and Zhao, Xiang, editor

Published
2023
Full Text
View/download PDF

5. MOTOR TOLERANCE OPTIMIZATION DESIGN BASED ON IMPROVED GENETIC ALGORITHM

Author

ZHANG YongLiang, CHEN Xu, YAO JiaSheng, and ZHANG ShuaiShuai

Subjects
Tolerance, Multi-objective optimization, Genetic algorithm, Motor assembly, Optimization model, Mechanical engineering and machinery, TJ1-1570, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

In order to improve the assembly quality of the motor and reduce the total cost,it is necessary to optimize the design of the tolerances of the key components that form the air gap between the motor stator and the rotor. A multi-objective and multi-constrained mathematical model for radial tolerance optimization of a motor assembly was established with processing cost and mass loss cost as objective functions,tolerance values of key components as design variables,and assembly functions and economic processing capabilities as constraints. The model was solved based on the improved genetic algorithm,and the key component tolerances under the lowest total were obtained. Through CETOL 6σ simulation verification,the results show that the passing rate of motor assembly is increased by about 55. 7%,and the total cost is reduced by about 45. 2% with the optimized design tolerance.

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results