The Use of Artificial Intelligence in Tribology-A Perspective

被引：122

作者：

Rosenkranz, Andreas ^{[1
]}

Marian, Max ^{[2
]}

Profito, Francisco J. ^{[3
]}

Aragon, Nathan ^{[4
]}

Shah, Raj ^{[4
]}

机构：

[1] Univ Chile, Dept Chem Engn Biotechnol & Mat, Santiago 7820436, Chile

[2] Friedrich Alexander Univ Erlangen Nuremberg FAU, Engn Design, D-91058 Erlangen, Germany

[3] Univ Sao Paulo, Dept Mech Engn, Polytech Sch, BR-17033360 Sao Paulo, Brazil

[4] Koehler Instrument Co, Holtsville, NY 11742 USA

来源：

LUBRICANTS | 2021年 / 9卷 / 01期

关键词：

artificial intelligence; machine learning; artificial neural networks; tribology; NEURAL-NETWORK PREDICTION; WEAR; BEHAVIOR; COMPOSITES; FIBER;

D O I：

10.3390/lubricants9010002

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Artificial intelligence and, in particular, machine learning methods have gained notable attention in the tribological community due to their ability to predict tribologically relevant parameters such as, for instance, the coefficient of friction or the oil film thickness. This perspective aims at highlighting some of the recent advances achieved by implementing artificial intelligence, specifically artificial neutral networks, towards tribological research. The presentation and discussion of successful case studies using these approaches in a tribological context clearly demonstrates their ability to accurately and efficiently predict these tribological characteristics. Regarding future research directions and trends, we emphasis on the extended use of artificial intelligence and machine learning concepts in the field of tribology including the characterization of the resulting surface topography and the design of lubricated systems.

引用

页码：1 / 11

页数：11

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