{"title":"Multi-objective optimization of three-stage running-in process for main bearing of marine diesel engine","authors":"","doi":"10.1115/1.4062298","DOIUrl":null,"url":null,"abstract":"\n Running-in quality can be improved by optimizing the running-in parameters (load, speed and running-in time). The relationship between running-in quality and the fractal dimensions of friction signal and wear surface is analyzed. It shows that the larger the fractal dimension, the better the running-in quality. A multi-objective optimization design of the running-in parameters of the main bearing is carried out, using a non-dominated sorting genetic algorithm with elite strategy. The optimization targets are the large fractal dimension of friction coefficient, the large fractal dimension of wear surface, and small running-in time. It shows that the selection principles of running-in parameters are different for different stages and priorities. The optimal running-in parameters listed in this paper provides a specific reference to the optimal design of the three-stage running in of main bearing.","PeriodicalId":17586,"journal":{"name":"Journal of Tribology-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Tribology-transactions of The Asme","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4062298","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 1
Abstract
Running-in quality can be improved by optimizing the running-in parameters (load, speed and running-in time). The relationship between running-in quality and the fractal dimensions of friction signal and wear surface is analyzed. It shows that the larger the fractal dimension, the better the running-in quality. A multi-objective optimization design of the running-in parameters of the main bearing is carried out, using a non-dominated sorting genetic algorithm with elite strategy. The optimization targets are the large fractal dimension of friction coefficient, the large fractal dimension of wear surface, and small running-in time. It shows that the selection principles of running-in parameters are different for different stages and priorities. The optimal running-in parameters listed in this paper provides a specific reference to the optimal design of the three-stage running in of main bearing.
期刊介绍：
The Journal of Tribology publishes over 100 outstanding technical articles of permanent interest to the tribology community annually and attracts articles by tribologists from around the world. The journal features a mix of experimental, numerical, and theoretical articles dealing with all aspects of the field. In addition to being of interest to engineers and other scientists doing research in the field, the Journal is also of great importance to engineers who design or use mechanical components such as bearings, gears, seals, magnetic recording heads and disks, or prosthetic joints, or who are involved with manufacturing processes.
Scope: Friction and wear; Fluid film lubrication; Elastohydrodynamic lubrication; Surface properties and characterization; Contact mechanics; Magnetic recordings; Tribological systems; Seals; Bearing design and technology; Gears; Metalworking; Lubricants; Artificial joints
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