Reliability design and optimization of the planetary gear by a GA based on the DEM and Kriging model

Da Cui, Guoqiang Wang, Yanpeng Lu and Kangkang Sun

Reliability Engineering and System Safety, 2020, vol. 203, issue C

Abstract: Based on stress-strength interference theory, calculating the reliability by using the coefficient of variation is a common method for the optimal design of a planetary transmission system. This method calculates the reliability by assuming the tangential force is zero while this is quite different from the real working condition. In this paper, the authors propose a novel reliability design and optimization method of the planetary gear, using the genetic algorithm, based on Kriging model. The Kriging method is used to establish the gear reliability model to simplify the reliability calculation. Then the Kriging model is optimized by using the genetic algorithm to ensure the global optimal solution. To simulate the real working conditions of planetary gears, the discrete element method (DEM) is adopted to calculates the load variation coefficient of the planetary gear. By taking the double toothed roller crusher as case study, the optimization results show that proposed method can significantly improve the calculation efficiency, and compared with the traditional design, the volume increases by 36.96%, and the failure rate of the planetary gear decreases by 17.05%.

Keywords: Planetary gear reliability optimization; Discrete element method (DEM); Kriging model; Genetic algorithm; Coefficient of variation (COV) (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832020305755
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:203:y:2020:i:c:s0951832020305755

DOI: 10.1016/j.ress.2020.107074

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().