{"title":"磨损建模与摩擦噪声:综述","authors":"Yang Tian, Muhammad Khan, Hao Yuan, Bohao Zheng","doi":"10.26599/frict.2025.9441124","DOIUrl":null,"url":null,"abstract":"<p>Wear and friction-induced noise are pivotal tribological phenomena that significantly influence the longevity and efficiency of mechanical systems. This review synthesizes current research on wear modeling and friction-induced noise, exploring their mechanisms, influencing factors, and predictive challenges. Wear modeling encompasses a range of approaches, from traditional methods such as the Archard equation to more advanced numerical and machine learning techniques. These models address diverse mechanisms—adhesive, abrasive, and fatigue wear—which are shaped by material properties, surface roughness, and environmental conditions. Friction-induced noise, arising from stick-slip, sprag-slip, and mode-coupling, is influenced by surface states, damping, and operational parameters. Crucially, wear and noise are interlinked. Wear reshapes surfaces and dynamics, thereby modulating noise, while noise can serve as a diagnostic tool for wear progression. Yet, existing models often isolate these phenomena, neglecting their synergy and impeding accurate system-life predictions. This review highlights this gap and advocates for the development of integrated wear-noise models, harnessing multiscale simulations, advanced computation, and empirical validation. The development of such models has the potential to significantly enhance the accuracy of durability and acoustic performance predictions. They offer a holistic framework that captures the dynamic interplay between surface degradation and noise generation. This framework is essential for advancing non-invasive detection technologies in industries such as automotive, aerospace, and manufacturing. In these sectors, addressing these dual challenges is crucial for enhancing performance, safety, and efficiency.</p>","PeriodicalId":12442,"journal":{"name":"Friction","volume":"2 1","pages":""},"PeriodicalIF":6.3000,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wear modeling and friction-induced noise: A review\",\"authors\":\"Yang Tian, Muhammad Khan, Hao Yuan, Bohao Zheng\",\"doi\":\"10.26599/frict.2025.9441124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Wear and friction-induced noise are pivotal tribological phenomena that significantly influence the longevity and efficiency of mechanical systems. This review synthesizes current research on wear modeling and friction-induced noise, exploring their mechanisms, influencing factors, and predictive challenges. Wear modeling encompasses a range of approaches, from traditional methods such as the Archard equation to more advanced numerical and machine learning techniques. These models address diverse mechanisms—adhesive, abrasive, and fatigue wear—which are shaped by material properties, surface roughness, and environmental conditions. Friction-induced noise, arising from stick-slip, sprag-slip, and mode-coupling, is influenced by surface states, damping, and operational parameters. Crucially, wear and noise are interlinked. Wear reshapes surfaces and dynamics, thereby modulating noise, while noise can serve as a diagnostic tool for wear progression. Yet, existing models often isolate these phenomena, neglecting their synergy and impeding accurate system-life predictions. This review highlights this gap and advocates for the development of integrated wear-noise models, harnessing multiscale simulations, advanced computation, and empirical validation. The development of such models has the potential to significantly enhance the accuracy of durability and acoustic performance predictions. They offer a holistic framework that captures the dynamic interplay between surface degradation and noise generation. This framework is essential for advancing non-invasive detection technologies in industries such as automotive, aerospace, and manufacturing. In these sectors, addressing these dual challenges is crucial for enhancing performance, safety, and efficiency.</p>\",\"PeriodicalId\":12442,\"journal\":{\"name\":\"Friction\",\"volume\":\"2 1\",\"pages\":\"\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Friction\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.26599/frict.2025.9441124\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Friction","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.26599/frict.2025.9441124","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Wear modeling and friction-induced noise: A review
Wear and friction-induced noise are pivotal tribological phenomena that significantly influence the longevity and efficiency of mechanical systems. This review synthesizes current research on wear modeling and friction-induced noise, exploring their mechanisms, influencing factors, and predictive challenges. Wear modeling encompasses a range of approaches, from traditional methods such as the Archard equation to more advanced numerical and machine learning techniques. These models address diverse mechanisms—adhesive, abrasive, and fatigue wear—which are shaped by material properties, surface roughness, and environmental conditions. Friction-induced noise, arising from stick-slip, sprag-slip, and mode-coupling, is influenced by surface states, damping, and operational parameters. Crucially, wear and noise are interlinked. Wear reshapes surfaces and dynamics, thereby modulating noise, while noise can serve as a diagnostic tool for wear progression. Yet, existing models often isolate these phenomena, neglecting their synergy and impeding accurate system-life predictions. This review highlights this gap and advocates for the development of integrated wear-noise models, harnessing multiscale simulations, advanced computation, and empirical validation. The development of such models has the potential to significantly enhance the accuracy of durability and acoustic performance predictions. They offer a holistic framework that captures the dynamic interplay between surface degradation and noise generation. This framework is essential for advancing non-invasive detection technologies in industries such as automotive, aerospace, and manufacturing. In these sectors, addressing these dual challenges is crucial for enhancing performance, safety, and efficiency.
期刊介绍:
Friction is a peer-reviewed international journal for the publication of theoretical and experimental research works related to the friction, lubrication and wear. Original, high quality research papers and review articles on all aspects of tribology are welcome, including, but are not limited to, a variety of topics, such as:
Friction: Origin of friction, Friction theories, New phenomena of friction, Nano-friction, Ultra-low friction, Molecular friction, Ultra-high friction, Friction at high speed, Friction at high temperature or low temperature, Friction at solid/liquid interfaces, Bio-friction, Adhesion, etc.
Lubrication: Superlubricity, Green lubricants, Nano-lubrication, Boundary lubrication, Thin film lubrication, Elastohydrodynamic lubrication, Mixed lubrication, New lubricants, New additives, Gas lubrication, Solid lubrication, etc.
Wear: Wear materials, Wear mechanism, Wear models, Wear in severe conditions, Wear measurement, Wear monitoring, etc.
Surface Engineering: Surface texturing, Molecular films, Surface coatings, Surface modification, Bionic surfaces, etc.
Basic Sciences: Tribology system, Principles of tribology, Thermodynamics of tribo-systems, Micro-fluidics, Thermal stability of tribo-systems, etc.
Friction is an open access journal. It is published quarterly by Tsinghua University Press and Springer, and sponsored by the State Key Laboratory of Tribology (TsinghuaUniversity) and the Tribology Institute of Chinese Mechanical Engineering Society.