文章基本信息

标题：Module Failure Feature Detection by Cluster Analysis for Fleets of Civil Aircraft Engines ⁎
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作者：Hang Zhou ; Alexandra Brintrup ; Ajith Kumar Parlikad 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：1
页码：31-36
DOI：10.1016/j.ifacol.2021.08.154
语种：English
出版社：Elsevier
摘要：AbstractDuring the operation of airplanes in the aviation industry, the stochastic environment in which the airplanes are being operated creates high complexity in planning the fleet overhauls for the aircraft engines. In order to perform efficient and cost-effective overhauls, the maintenance approach is to exchange the modules that caused the removal of engines from airplanes. Typical civil aviation engine consists of eight modules, in order to avoid disturbance for engine end users (airlines), all the modules should be available and well planed in any period of time window. This paper aims to provide a module planning solution based on the fleet operational history of aircraft engines, in order to cluster the engine performances into featured zones for overhaul module demand estimation.
关键词：Keywordscluster analysisunsupervised learningaerospace engineeringmaintenance