{"title":"指定三维粗糙度空间参数的喷丸强化零件三维粗糙表面形貌数值模拟新方法","authors":"Jiling Chen, Jinyuan Tang, Wen Shao, Xin Li, Jiuyue Zhao, Wei Zhou, Ding Zhang","doi":"10.1007/s11249-024-01921-w","DOIUrl":null,"url":null,"abstract":"<div><p>According to random process theory, the existing autocorrelation function (ACF) expression that characterizes the spatial features of the shot peening (SP) surface topography makes it difficult to constrain the 3D roughness spatial parameters defined in ISO 25178, which restricts the correlation studies between surface topography and service performance. This paper introduces a new ACF expression for reconstructing the SP surface topography with specified spatial parameters. Based on the new expression, a numerical simulation method for stratified surface topography applicable to SP after finishing is introduced. The main idea is to perform feature extraction and feature modeling on the measured surface with the help of machine learning. The new method is applied to the numerical simulation of the SP and grinding-shot peening (Gr-SP) surface topography with a coverage of 200%. The relative error in height distribution and spatial parameters between the measured and simulated surface topography are less than 5%. The new method of height distribution and spatial parameters active design is provided to study the correlation between surface topography and service performance of shot peening parts.</p><h3>Graphical Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":806,"journal":{"name":"Tribology Letters","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Numerical Simulation Method for 3D Rough Surface Topography of Shot Peening Parts with Specified 3D Roughness Spatial Parameters\",\"authors\":\"Jiling Chen, Jinyuan Tang, Wen Shao, Xin Li, Jiuyue Zhao, Wei Zhou, Ding Zhang\",\"doi\":\"10.1007/s11249-024-01921-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>According to random process theory, the existing autocorrelation function (ACF) expression that characterizes the spatial features of the shot peening (SP) surface topography makes it difficult to constrain the 3D roughness spatial parameters defined in ISO 25178, which restricts the correlation studies between surface topography and service performance. This paper introduces a new ACF expression for reconstructing the SP surface topography with specified spatial parameters. Based on the new expression, a numerical simulation method for stratified surface topography applicable to SP after finishing is introduced. The main idea is to perform feature extraction and feature modeling on the measured surface with the help of machine learning. The new method is applied to the numerical simulation of the SP and grinding-shot peening (Gr-SP) surface topography with a coverage of 200%. The relative error in height distribution and spatial parameters between the measured and simulated surface topography are less than 5%. The new method of height distribution and spatial parameters active design is provided to study the correlation between surface topography and service performance of shot peening parts.</p><h3>Graphical Abstract</h3>\\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>\",\"PeriodicalId\":806,\"journal\":{\"name\":\"Tribology Letters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tribology Letters\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11249-024-01921-w\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tribology Letters","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s11249-024-01921-w","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
A New Numerical Simulation Method for 3D Rough Surface Topography of Shot Peening Parts with Specified 3D Roughness Spatial Parameters
According to random process theory, the existing autocorrelation function (ACF) expression that characterizes the spatial features of the shot peening (SP) surface topography makes it difficult to constrain the 3D roughness spatial parameters defined in ISO 25178, which restricts the correlation studies between surface topography and service performance. This paper introduces a new ACF expression for reconstructing the SP surface topography with specified spatial parameters. Based on the new expression, a numerical simulation method for stratified surface topography applicable to SP after finishing is introduced. The main idea is to perform feature extraction and feature modeling on the measured surface with the help of machine learning. The new method is applied to the numerical simulation of the SP and grinding-shot peening (Gr-SP) surface topography with a coverage of 200%. The relative error in height distribution and spatial parameters between the measured and simulated surface topography are less than 5%. The new method of height distribution and spatial parameters active design is provided to study the correlation between surface topography and service performance of shot peening parts.
期刊介绍：
Tribology Letters is devoted to the development of the science of tribology and its applications, particularly focusing on publishing high-quality papers at the forefront of tribological science and that address the fundamentals of friction, lubrication, wear, or adhesion. The journal facilitates communication and exchange of seminal ideas among thousands of practitioners who are engaged worldwide in the pursuit of tribology-based science and technology.
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