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Civil aircraft health management research based on big data and deep learning technologies

机译:基于大数据和深度学习技术的民用飞机健康管理研究

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The coupling and correlation degree between aircraft systems is higher, and the diagnosis and prognosis of aircraft are more complex. Building a platform for storing and analyzing the aviation big data becomes an important task for civil aviation. This paper proposes a civil aircraft health management big data architecture. The civil aircraft health management system includes airborne PHM, ground PHM, remote diagnosis system, portable maintenance assistant system, maintenance center, automatic test equipment, special test equipment. Airborne PHM collects data from multiple types of data sources. Ground PHM provides decision making support for civil aircrafts including real-time alarm, health management, maintenance plan, spare parts. The paper introduces deep learning algorithm and aircraft fault diagnosis and prognosis implementation.
机译:飞机系统之间的耦合度和相关度较高,飞机的诊断和预后更为复杂。建立存储和分析航空大数据的平台已成为民航的一项重要任务。本文提出了一种民用飞机健康管理大数据架构。民用飞机健康管理系统包括机载PHM,地面PHM,远程诊断系统,便携式维护助手系统,维护中心,自动测试设备,专用测试设备。机载PHM从多种类型的数据源中收集数据。地面PHM为民用飞机提供决策支持,包括实时警报,健康管理,维护计划,备件。本文介绍了深度学习算法以及飞机故障的诊断和预后实现。

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