Müge Gürgen, Mete Bakır, Ersin Bahceci, Hakkı Özgür Ünver
{"title":"从基于物理的模型到人工智能辅助模型在工业应用中的疲劳预测综述","authors":"Müge Gürgen, Mete Bakır, Ersin Bahceci, Hakkı Özgür Ünver","doi":"10.1504/ijmms.2023.133400","DOIUrl":null,"url":null,"abstract":"For a mechanical part to be certified, it should be assessed whether its mechanical, optical or thermal properties satisfy service requirements. Fatigue is one of the critical properties of functional materials, particularly in the aviation industry, where new materials, such as alloys, fibre-reinforced composites and additively manufactured alloys, dominate increasingly. This trend puts a heavy burden on fatigue characterisation, which is expensive and time-consuming. However, recent developments in artificial intelligence offer novel methods to decrease the test load cost-effectively. Hence, this literature survey first summarises predominant fatigue models both theoretical and numerical, and then covers and classifies recent studies (2000-2023) using recent machine learning techniques.","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A review from physics based models to artificial intelligence aided models in fatigue prediction for industry applications\",\"authors\":\"Müge Gürgen, Mete Bakır, Ersin Bahceci, Hakkı Özgür Ünver\",\"doi\":\"10.1504/ijmms.2023.133400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For a mechanical part to be certified, it should be assessed whether its mechanical, optical or thermal properties satisfy service requirements. Fatigue is one of the critical properties of functional materials, particularly in the aviation industry, where new materials, such as alloys, fibre-reinforced composites and additively manufactured alloys, dominate increasingly. This trend puts a heavy burden on fatigue characterisation, which is expensive and time-consuming. However, recent developments in artificial intelligence offer novel methods to decrease the test load cost-effectively. Hence, this literature survey first summarises predominant fatigue models both theoretical and numerical, and then covers and classifies recent studies (2000-2023) using recent machine learning techniques.\",\"PeriodicalId\":39429,\"journal\":{\"name\":\"International Journal of Mechatronics and Manufacturing Systems\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Mechatronics and Manufacturing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijmms.2023.133400\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mechatronics and Manufacturing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijmms.2023.133400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
A review from physics based models to artificial intelligence aided models in fatigue prediction for industry applications
For a mechanical part to be certified, it should be assessed whether its mechanical, optical or thermal properties satisfy service requirements. Fatigue is one of the critical properties of functional materials, particularly in the aviation industry, where new materials, such as alloys, fibre-reinforced composites and additively manufactured alloys, dominate increasingly. This trend puts a heavy burden on fatigue characterisation, which is expensive and time-consuming. However, recent developments in artificial intelligence offer novel methods to decrease the test load cost-effectively. Hence, this literature survey first summarises predominant fatigue models both theoretical and numerical, and then covers and classifies recent studies (2000-2023) using recent machine learning techniques.
期刊介绍:
IJMMS publishes refereed quality papers in the broad field of mechatronics and manufacturing systems with a special emphasis on research and development in the modern engineering of advanced manufacturing processes and systems. IJMMS fosters information exchange and discussion on all aspects of mechatronics (computers, electrical and mechanical engineering) with applications in manufacturing processes and systems.