Parameter-based RNN micro-interface inversion model for wet friction components morphology

Parameter-based RNN micro-interface inversion model for wet friction components morphology

The interface morphology significantly impact the service life of wet clutches friction components in heavy tracked vehicle transmission systems. This paper designs a sliding test and utilizes a recurrent neural network (RNN) model to construct the three-dimensional morphology of the wet clutch fric...

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Bibliographic Details
Main Authors: Jianpeng Wu, Yuxin Wang, Chengbing Yang, Xiaozan Huang, Liyong Wang
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Alexandria Engineering Journal
Subjects:
Micro-interface morphology
The RNN inversion model
Working condition parameters
Wet friction components
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016824010159
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