航空学报 > 2014, Vol. 35 Issue (6): 1459-1472   doi: 10.7527/S1000-6893.2013.0548

大型飞机机载系统预测与健康管理关键技术

王少萍   

  1. 北京航空航天大学 自动化科学与电气工程学院, 北京 100191
  • 收稿日期:2014-01-03 修回日期:2014-02-17 出版日期:2014-06-25 发布日期:2014-02-26
  • 通讯作者: 王少萍,Tel.:010-82338933 E-mail:shaopingwang@vip.sina.com E-mail:shaopingwang@vip.sina.com
  • 作者简介:王少萍女,博士,教授,博士生导师。主要研究方向:故障诊断与可靠性,机电控制与仿真。Tel:010-82338933E-mail:shaopingwang@vip.sina.com
  • 基金资助:

    国家“973”计划(2014CB046402);国家自然科学基金(51175014);国家“111”计划

Prognostics and Health Management Key Technology of Aircraft Airborne System

WANG Shaoping   

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
  • Received:2014-01-03 Revised:2014-02-17 Online:2014-06-25 Published:2014-02-26
  • Supported by:

    National Basic Research Program of China (2014CB046402); National Natural Science Foundation of China (51175014); Programme of Introducing Talents of Discipline Universities of China.

摘要:

为确保飞机的高可靠性、高安全性和高维修保障性,大型飞机机载系统均装备了先进的故障预测与健康管理(PHM)系统,以实现高可靠运行和健康服役。从大型飞机健康管理体系结构入手,介绍了基于国际标准分层开放式的故障预测与健康管理空地结构,及其开放式、模块化和标准接口规范。着重分析了机载健康管理传感器网络和鲁棒故障特征提取方法、分层聚类和交叉增强校核的智能故障诊断算法和基于数据驱动与失效物理结合的故障预测算法等关键技术,探讨了基于健康状态的维修保障决策方法。最后,给出了空地一体的飞机故障预测与健康管理评价方法和健康管理技术的适用性分析。

关键词: 飞机机载系统, 故障诊断推理, 故障预测, 健康管理, 维修保障评价

Abstract:

In order to guarantee high reliability, safety and supportability of passenger aircraft, they are usually equipped with prognostics and health management (PHM) to realize reliable operation and health service. This paper introduces the prognostics and health management structure based on on-board monitoring system, air-ground data link and ground maintenance management system under open standards and three-level reasoning. With the multiple data resources from on-board sensors network, historical flight data and maintenance data, this paper gives the way to extract the failure features robustly. Through the hierarchy design, aircraft prognostics and health management adopts the intelligent fault diagnosis algorithm based on hierarchy clustering and enhanced cross check to realize high precision fault diagnosis and isolation. Even in the aircraft health service, the prognostics and health management can also predict the failure based on data driven reasoning, knowledge and failure physics, and then provide the condition-based maintenance strategy. Finally, this paper gives the prognostics and health management evaluation and applicability analysis of the corresponding technology of PHM.

Key words: aircraft airborne system, fault diagnosis reasoning, failure prediction, health management, supportability evaluation

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