Machine Learning Algorithms for Predicting Wear Rates on the Basis of Friction Noise-Reference-Cited by-同舟云学术

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Machine Learning Algorithms for Predicting Wear Rates on the Basis of Friction Noise

Published:2024-07-03 Issue:4 Volume:67 Page:730-743
ISSN:1040-2004
Container-title:Tribology Transactions
language:en
Short-container-title:Tribology Transactions

Author:

Zhao Honghao¹²,Yang Zi²,Zhang Bo³,Xiang Chong²,Guo Fei²

Affiliation:

1. Department of Mechanical Engineering, Harbin Institute of Technology at Weihai, Weihai, P. R. China

2. State Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing, P. R. China

3. Guangzhou Mechanical Engineering Research Institute Co., Ltd, Guangzhou, P. R. China

Funder

the National Natural Science Foundation of China

the Independent Research Project of State Key Laboratory of Tribology in Advanced Equipment

the Major National R&D Projects of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10402004.2024.2336005

Reference39 articles.

1. Modelling of Frictional Phenomena using Neural Networks: Friction Coefficient Estimation

2. Adhesive wear behaviour of cast aluminium–silicon alloys: Overview

3. Machine Learning and Statistical Approach to Predict and Analyze Wear Rates in Copper Surface Composites

4. Accessing Inaccessible Interfaces: In Situ Approaches to Materials Tribology

5. The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection

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