A double-layer iterative analytical model for mesh stiffness and load distribution of early-stage cracked gear based on the slicing method

Lantao Yang, Liming Wang, Yimin Shao, Fengshou Gu, Andrew Ball, David Mba

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

To reveal the coupling relationship between the time-varying mesh stiffness (TVMS) and the load distribution along the tooth width direction (TWD) of gears with early-stage crack (ESC), a double-layer iterative analytical model for the TVMS and load distributions of gears is proposed considering the effects of the non-uniformly distributed load (NDL) along TWD caused by the ESC. In the proposed model, an analytical model of tooth torsional deformation and a parallel slice stiffness model of the tooth pair with ESC are separately developed based on the slicing method. On this basis, a double-layer iterative calculation method for the TVMS and load distributions is proposed, in which the coupling relationships between the slice stiffness and load distribution along TWD as well as the TVMS and load distribution between the meshing tooth pairs are respectively presented with the inner- and outer- layer iterations. Finite element (FE) models are established to verify the proposed double-layer iterative model. The effects of crack parameters and applied torque on the tooth torsional deformation, TVMS, and load distributions of the gear with ESC are finally investigated based on the proposed model. The results show that the proposed model can realize the accurate and fast decoupling calculation of the TVMS and load distributions of gears with ESC. This study can provide a basis for the establishment of the refined ESC fault diagnosis method and the rapid evaluation of the load distributions of gears with asymmetric errors or faults along TWD.

Original languageEnglish
Article number110456
Number of pages28
JournalMechanical Systems and Signal Processing
Volume198
Early online date25 May 2023
DOIs
Publication statusPublished - 1 Sep 2023

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