Dynamic Model of Planetary Gear with Consideration of Tooth Surface Roughness

Jirui Zhu, Dong Zhen, Xiaoxia Liang, Guojin Feng, Fengshou Gu, Andrew D. Ball

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Planetary gearbox is numerously used in various mechanical transmission systems because of their extensive bearing range and high reliability. However, due to limitations in manufacturing technique and economic considerations, the gear tooth surface roughness inevitable exists in practical manufacturing process. To analyze the influence of the tooth surface roughness on the vibration signals of a planetary gear system, a nonlinear dynamic model considering multi-factor coupling is established. The dynamic model takes into account gear tooth surface roughness, the gear backlash, time-varying meshing stiffness (TVMS) and vibration transfer path. Via this nonlinear model, the effects of different tooth surface roughness on the system dynamics response are analyzed. Furthermore, the dynamic responses in the time domain and frequency domain are used to examine the influences in the main dynamic parameters, such as rotational speed and meshing force. The results show that the tooth surface roughness significantly affect the system dynamic characteristics, and with the increase of the roughness, the influence on the response of the system will enlarge. This paper can offer some theoretic guidance for the development, operation and fault identification of planetary gear transmission system.

Original languageEnglish
Title of host publicationProceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022
EditorsChuan Li, Gianluca Valentino, Ling Kang, Diego Cabrera, Dejan Gjorgjevikj
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages176-181
Number of pages6
ISBN (Electronic)9781665479547
ISBN (Print)9781665479554
DOIs
Publication statusPublished - 1 Jul 2022
Event2022 Prognostics and Health Management Conference - London, United Kingdom
Duration: 27 May 202229 May 2022

Publication series

NameProceedings - 2022 Prognostics and Health Management Conference, PHM-London 2022
PublisherIEEE
ISSN (Print)2166-563X
ISSN (Electronic)2166-5656

Conference

Conference2022 Prognostics and Health Management Conference
Abbreviated titlePHM-London 2022
Country/TerritoryUnited Kingdom
CityLondon
Period27/05/2229/05/22

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