Neural-driven viscosity modeling and fatigue optimization for cycloidal gear systems

IF 6.1 1区工程技术 Q1 ENGINEERING, MECHANICAL

Tribology International Pub Date : 2024-10-11 DOI:10.1016/j.triboint.2024.110311

Ning Jiang , Rundong Qian , Haiyu Qiao , Yani Chen , Honghui Cao , Yayun Liu , Chuanyang Wang

引用次数: 0

Abstract

This study presents a comprehensive approach to enhancing RV reducer performance. A novel RAM viscosity-pressure model is developed, combining traditional stability with neural network precision. Surface micro-morphological analysis is integrated with contact fatigue modeling, revealing critical insights into surface characteristics and their impact on fatigue. A neural proxy-based optimization strategy is employed to identify optimal operational parameters, significantly reducing fatigue risks. Additionally, a new method for real-time transmission ratio monitoring is introduced, validating the model's effectiveness and offering a robust framework for improving the reliability and lifespan of RV reducers in industrial applications.

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摆线齿轮系统的神经驱动粘度建模和疲劳优化

本研究提出了一种提高 RV 减速器性能的综合方法。结合传统稳定性和神经网络精度，开发了一种新型 RAM 粘压模型。表面微观形态分析与接触疲劳建模相结合，揭示了表面特征及其对疲劳影响的重要见解。采用基于神经代理的优化策略来确定最佳运行参数，从而大大降低了疲劳风险。此外，还引入了一种用于实时传动比监测的新方法，从而验证了模型的有效性，并为提高工业应用中 RV 减速器的可靠性和使用寿命提供了一个稳健的框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Tribology International 工程技术-工程：机械

CiteScore

10.10

自引率

16.10%

发文量

627

审稿时长

35 days

期刊介绍： Tribology is the science of rubbing surfaces and contributes to every facet of our everyday life, from live cell friction to engine lubrication and seismology. As such tribology is truly multidisciplinary and this extraordinary breadth of scientific interest is reflected in the scope of Tribology International. Tribology International seeks to publish original research papers of the highest scientific quality to provide an archival resource for scientists from all backgrounds. Written contributions are invited reporting experimental and modelling studies both in established areas of tribology and emerging fields. Scientific topics include the physics or chemistry of tribo-surfaces, bio-tribology, surface engineering and materials, contact mechanics, nano-tribology, lubricants and hydrodynamic lubrication.