This review discusses optimization of surface texture and its effects on friction in rolling bearings, suggesting future AI enhancements.
Surface texture refers to the process of creating a series of microstructures with a specific distribution pattern and size on the surface of mechanical components using machining equipment. This technique improves the lubrication, friction, and wear performance of contact surfaces. Researchers have conducted extensive optimization of surface texture geometric features and operating conditions to study the mechanisms and applications of surface texture technology. This paper reviews the development and processing methods of surface texture technology, as well as the main research achievements in controlling rolling bearing friction in recent years. It discusses the latest advances in improving the tribological performance of material surfaces from two aspects: the geometric features of surface texture and practical operating conditions. The geometric features include the shape, diameter, depth, areal density, and arrangement of the surface texture. Practical operating conditions depend on the type of friction and operational conditions. An analysis and summary of the parameters and conditions that improve surface tribological performance are presented. The paper also reveals the mechanism of laser surface texture’s effect on the friction and wear performance of rolling bearings. Future research will need to extend the test duration, optimize texture parameters (such as external profile, size, bottom shape, and laser parameters), and apply artificial intelligence algorithms like deep learning and neural networks. These areas will be the focus of future research.
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Wang et al. (2025) studied this question.
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