Characteristic sensitivity analysis of herringbone gear power-split transmission system

ABSTRACT

The herringbone gear power-split transmission is widely used in high-speed and heavy-load transmission systems, and its dynamic analysis is becoming increasingly important. The characteristic sensitivity of a gear transmission system indicates the influence of the dynamic parameters on the natural frequency of the gear transmission system, and it functions as an important theoretical reference value in the dynamic design of a herringbone gear power-split transmission system. In this paper, the dynamic equations of a herringbone gear power-split transmission system for a ship are presented, and the natural frequencies and modal shapes are calculated based on the free torsional vibration differential equation. Subsequently, the modal shapes were classified into the coupling vibration model and the branch vibration model. The characteristic sensitivity was studied using modal analysis, and the characteristic sensitivity calculation equations for single and double root of natural frequency were deduced, and the characteristic sensitivity of the natural frequencies to the mesh stiffness was computed. Finally, the relationship between the modal strain energy and the characteristic sensitivity was analysed, and the physics essence of the characteristic sensitivity was revealed.

KEYWORDS:

• Herringbone gear
• power-split transmission
• characteristic sensitivity
• natural frequency
• modal shape

Disclosure of interest

No potential conflict of interest was reported by the author(s).

Data Availability Statement

All data generated or analysed during this study are included in this published article. The data have been deposited in Figshare (https://doi.org/10.6084/m9.figshare.14478966.v2 and https://doi.org/10.6084/m9.figshare.14479107.v1). Requests for material should be made to the corresponding authors.

Additional information

Funding

This work was supported by the Doctoral Scientific Research Starting Foundation of Northwest A&F University under Grant 2452018003 and the Science and Technology Project of Yangling (2018NY-20). The authors would like to thank Editage [www.editage.cn] for English language editing.