{"title":"Addressing Gearbox Health Monitoring Challenges for Helicopters: A Machine Learning Approach.","authors":"Guilherme Moreira, Alexandre Pereira, Airton Nabarrete, Willer Gomes","doi":"10.1590/0001-3765202420240404","DOIUrl":null,"url":null,"abstract":"<p><p>The transmission gearbox of military helicopters, such as the H225M, experiences intense dynamic loads, leading to the detachment of ferromagnetic particles, often due to wear or fatigue. This poses safety risks, as excessive particle detachment demands stringent maintenance. To address this, the study applies machine learning algorithms to predict particle detachment using data from the Flight Data Recorder and Health and Usage Monitoring System. The approach aims to mitigate operational challenges faced by the Brazilian H225M fleet while considering aviation safety criteria and the pre-processing needs for an effective machine learning application.</p>","PeriodicalId":7776,"journal":{"name":"Anais da Academia Brasileira de Ciencias","volume":"96 suppl 3","pages":"e20240404"},"PeriodicalIF":1.1000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais da Academia Brasileira de Ciencias","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1590/0001-3765202420240404","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The transmission gearbox of military helicopters, such as the H225M, experiences intense dynamic loads, leading to the detachment of ferromagnetic particles, often due to wear or fatigue. This poses safety risks, as excessive particle detachment demands stringent maintenance. To address this, the study applies machine learning algorithms to predict particle detachment using data from the Flight Data Recorder and Health and Usage Monitoring System. The approach aims to mitigate operational challenges faced by the Brazilian H225M fleet while considering aviation safety criteria and the pre-processing needs for an effective machine learning application.
期刊介绍:
The Brazilian Academy of Sciences (BAS) publishes its journal, Annals of the Brazilian Academy of Sciences (AABC, in its Brazilianportuguese acronym ), every 3 months, being the oldest journal in Brazil with conkinuous distribukion, daking back to 1929. This scienkihic journal aims to publish the advances in scienkihic research from both Brazilian and foreigner scienkists, who work in the main research centers in the whole world, always looking for excellence.
Essenkially a mulkidisciplinary journal, the AABC cover, with both reviews and original researches, the diverse areas represented in the Academy, such as Biology, Physics, Biomedical Sciences, Chemistry, Agrarian Sciences, Engineering, Mathemakics, Social, Health and Earth Sciences.