[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120150-en":3,"doc-seo-120150-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120150,8796095461610,"Oliver","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Addressing Gearbox Health Monitoring Challenges for Helicopters - A Machine Learning Approach","Military helicopter transmission gearboxes, such as the H225M, experience intense dynamic loads that can cause detachment of ferromagnetic particles through wear and fatigue. Excessive particle shedding increases safety and maintenance burden, requiring strict inspection and overhaul actions. The study uses machine learning to predict particle detachment from Flight Data Recorder and Health and Usage Monitoring System data, aiming to reduce fleet operational challenges for the Brazilian H225M while aligning with aviation safety criteria and machine-learning preprocessing needs.","An Acad Bras Cienc (2024) 96(Suppl. 3): e20240404 DOI 10.1590/0001-3765202420240404  \nAnais da Academia Brasileira de Ciências | Annals of the Brazilian Academy of Sciences Printed ISSN 0001-3765 I Online ISSN 1678-2690 [www.scielo. br/aabc | www.fb.com/aabcjournal](www.scielo. br/aabc | www.fb.com/aabcjournal)  \nENGINEERING SCIENCES  \nAddressing Gearbox Health Monitoring Challenges for Helicopters: A Machine Learning Approach  \nGUILHERME MOREIRA, ALEXANDRE PEREIRA, AIRTON NABARRETE & WILLER GOMES  \nAbstract: The transmission gearbox of military helicopters, such asthe 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 preprocessing needs for an effective machine learning application.  \nKey words: Machine Learning, flight safety criteria, helicopter transmission system, Airbus H225M, failure prediction.  \nINTRODUCTION  \nOn April 29, 2016, a fatal accident took place in Norway with an EC 225 LP helicopter, produced by Airbus Helicopters, after an in-flight detachment of the main rotor hub from the main gearbox (MGB) (AIBN 2018) . Two months after the accident the European Union Aviation Safety Agency (EASA) issued an Airworthiness Directive (AD) to require flight prohibition for all manufacturer serial numbers of helicopters AS 332 L2 and EC 225 LP (EASA 2016b) . This precautionary measure was based on the investigation report which indicated metallurgical findings of fatigue and surface degradation of components inside the MGB of the helicopter. EASA authorized the return to operation of these helicopters, after four months, with the accomplishment of several required actions, which included among others the repetitive inspections of MGB particle detectors and oil filter after last flight of the  \nday, or at intervals not to exceed 10 flight hours, whichever occurs first (EASA 2016a) .  \nThe extensive and complex investigation conducted by the Accident Investigation Board Norway (AIBN) revealed that the accident was a result of a fatigue fracture in one of the eight second stage planet gears in theepicyclic module of the MGB. According to the investigation report, the fatigue fracture initiated from a surface micro-pit in the upper outer race of the bearing, propagating subsurface while producing a limited quantity of particles from spalling, before turning towards the gear teeth and fracturing the rim of the gear without being detected (AIBN 2018) . The detachment of particles from rotating machine components occurs mainly due to wear of the transmission mechanisms in the gearboxes of the helicopter. Not coincidentally, the standards of the Federal Aviation Administration (FAA) set as an airworthiness requirement for rotary-wing  \nAn Acad Bras Cienc (2024) 96(Suppl. 3)  \naircraft, that rotor drive system transmissionsand gearboxes utilizing ferromagnetic materials must be equipped with chip detectors designed to indicate the presence of ferromagnetic particles resulting from damage or excessive wear within the transmission or gearbox (FAA 2022) . One of the measures proposed by EASAto control and mitigate the risk of accidents with EC-225 EP helicopters after returning to operation is to collect small particles of detached metal, that is less than 1 millimeter in size and circulate in the oil line of the helicopter MGB. If the detached particles exceed certain criteria, observing their quantity, area, length, shape and material, flights must be interrupted and the MGB of the helicopter should be taken for overhaul, which means the manufacturer can conduct a","cbCaivHkFNqhDiLy","https://ap.wps.com/l/cbCaivHkFNqhDiLy","pdf",1343704,1,25,"English","en",105,"# Introduction\n## Rotor gearbox detachment risk and regulatory context\n## Fault detection via oil analysis and vibration monitoring\n## Gear diagnostics objectives and residual life estimation\n## Time-statistical methods for rotating machinery fault detection","[{\"question\":\"What problem does the study address in helicopter transmission gearboxes?\",\"answer\":\"It addresses the detachment of ferromagnetic particles caused by wear and fatigue in gearbox systems, which can create serious safety risks and heavy maintenance requirements.\"},{\"question\":\"How does the proposed method predict particle detachment?\",\"answer\":\"It applies machine learning algorithms using data collected from the Flight Data Recorder and the Health and Usage Monitoring System to forecast particle detachment.\"},{\"question\":\"Why are current inspections and overhauls logistically challenging?\",\"answer\":\"Although inspections of particle detectors and oil filters are necessary, performing gearbox overhauls before the Time Between Overhaul (TBO) can take the aircraft out of service for months, creating major logistical difficulties for operators.\"}]","Addressing Gearbox Health Monitoring Challenges for Helicopters - A Machine Learning Approach | PDF",1785728448,63,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"addressing-gearbox-health-monitoring-challenges-for-helicopters-a-machine-learning-approach","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/addressing-gearbox-health-monitoring-challenges-for-helicopters-a-machine-learning-approach/120150/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the study address in helicopter transmission gearboxes?","Question",{"text":75,"@type":76},"It addresses the detachment of ferromagnetic particles caused by wear and fatigue in gearbox systems, which can create serious safety risks and heavy maintenance requirements.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the proposed method predict particle detachment?",{"text":80,"@type":76},"It applies machine learning algorithms using data collected from the Flight Data Recorder and the Health and Usage Monitoring System to forecast particle detachment.",{"name":82,"@type":73,"acceptedAnswer":83},"Why are current inspections and overhauls logistically challenging?",{"text":84,"@type":76},"Although inspections of particle detectors and oil filters are necessary, performing gearbox overhauls before the Time Between Overhaul (TBO) can take the aircraft out of service for months, creating major logistical difficulties for operators.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]