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Journal Articles

Research on a stacking ensemble model with adaptive feature weighting for predicting the tribological properties of lubricating grease

Accepted Manuscript
Yanqiu Xia, Xuemin Cheng, Xin Feng, Chaoqi Liu
Journal: Journal of Tribology
Publisher: ASME
Article Type: Technical Briefs
J. Tribol.
Paper No: TRIB-24-1520
https://doi.org/10.1115/1.4068056
Published Online: February 25, 2025
... Contributed by the Tribology Division of ASME for publication in the J ournal of T ribology . 03 12 2024 13 02 2025 13 02 2025 25 02 2025 Artificial Intelligence Composites friction lubricant additives lubricants Machine Learning Natural Science Foundation...
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Topics: Composite materials, Friction, Machine learning, Tribology, Lithium, Lubricants, Optimization algorithms, Wear, Algorithms, Artificial intelligence
Journal Articles

Predictive modelling of real contact area on rough surfaces using deep artificial neural network

Accepted Manuscript
Siddharth Suman, Deepak K Prajapati
Journal: Journal of Tribology
Publisher: ASME
Article Type: Research Papers
J. Tribol.
Paper No: TRIB-24-1525
https://doi.org/10.1115/1.4068057
Published Online: February 25, 2025
... 2025 Artificial Intelligence contact area contact mechanics Machine Learning surface roughness and asperities Accepted Manuscript Not Copyedited Journal of Tribology. Received December 04, 2024; Accepted manuscript posted February 25, 2025. doi:10.1115/1.4068057 Copyright © 2025 by ASME...
View Article titled, Predictive modelling of real contact area on rough surfaces using deep artificial neural network
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Topics: Artificial neural networks, Contact mechanics, Modeling, Surface roughness
Journal Articles

Transfer Models and Standard Models for Predicting Wear-Rates on the Basis of Friction Noise: A Comparative Study

Honghao Zhao, Mingxuan Wang, Yuquan Liu, Ping Deng, Xin Hu, Fei Guo
Journal: Journal of Tribology
Publisher: ASME
Article Type: Research Papers
J. Tribol. June 2025, 147(6): 061702.
Paper No: TRIB-24-1517
https://doi.org/10.1115/1.4067816
Published Online: February 14, 2025
.... Transfer model usually refers to a technical approach in the field of machine learning and artificial intelligence, namely, transfer learning. The key to this technique is to improve the learning efficiency and effectiveness of one task by transferring the knowledge gained in one domain or task to another...
View Article titled, Transfer Models and Standard Models for Predicting Wear-Rates on the Basis of Friction Noise: A Comparative Study
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Topics: Algorithms, Friction, Noise (Sound), Wear, Feature selection
Journal Articles

Assessment of Tool Condition and Surface Quality Using Hybrid Deep Neural Network: CNN-LSTM-Based Segmentation and Statistical Analysis

K. Venkata Rao
Journal: Journal of Tribology
Publisher: ASME
Article Type: Research Papers
J. Tribol. August 2025, 147(8): 084201.
Paper No: TRIB-24-1479
https://doi.org/10.1115/1.4067496
Published Online: January 3, 2025
... abrasion artificial intelligence vibrations wear Tool wear and surface roughness have a significant effect on the product quality and machining efficiency. In the machining process, 20% of the machining time is interrupted due to tool failure problems that greatly affect the machining efficiency...
View Article titled, Assessment of Tool Condition and Surface Quality Using Hybrid Deep Neural Network: CNN-LSTM-Based Segmentation and Statistical Analysis
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Topics: Convolutional neural networks, Surface roughness, Vibration, Wear, Machining, Image segmentation
Journal Articles

Machine Learning in Wear Prediction

Raj Shah, Nikhil Pai, Gavin Thomas, Swarn Jha, Vikram Mittal, Khosro Shirvni, Hong Liang
Journal: Journal of Tribology
Publisher: ASME
Article Type: Review Articles
J. Tribol. April 2025, 147(4): 040801.
Paper No: TRIB-24-1270
https://doi.org/10.1115/1.4066865
Published Online: November 6, 2024
...: hliang@tamu.edu Contributed by the Tribology Division of ASME for publication in the J ournal of T ribology . 30 07 2024 30 09 2024 02 10 2024 06 11 2024 Graphical Abstract Figure artificial intelligence friction machine learning wear wear mechanisms...
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Topics: Artificial neural networks, Machine learning, Wear, Maintenance