基于健康管理技术的机载计算机智能故障诊断方法  

An Intelligent Fault Diagnosis Method for Airborne Computer Based on Health Management Technology

作　　者：马小博[1] 王芳 陈益[1] 李亚锋 Ma Xiaobo;Wang Fang;Chen Yi;Li Yafeng(Xi'an Aeronautics Computing Technique Research Institute,AVIC,Xi'an 710068,China;Air Force Equipment Department Sixth Military Delegate Room at Xi'an 710068,China)

机构地区：[1]西安航空计算技术研究所,西安710068 [2]空装驻西安地区军事代表局第六代表室,西安710068

出　　处：《计算机测量与控制》2019年第11期43-47,共5页Computer Measurement &Control

摘　　要：为了满足飞机机载电子设备以状态监控为基础的视情维修保障策略,提升设备可维护性,提出了一种基于在线检测、故障预测、辅助决策的健康监控管理故障诊断方法,支持对机载电子设备的健康状态进行预测和评估;通过划分机载电子设备子功能的敏感威胁区域,对这些区域设计专门的威胁预警监控电路,进行功能危害监控,建立推理监控模型对监控电路故障进行预警监控,结合辅助决策的方式对预警到的故障进行定位,实现对电子设备的智能故障诊断;通过FMEA的分析与故障注入测试验证,该预警电路、推理模型和辅助决策能有效的预测故障及定位,具有较高的故障预测覆盖率,可提高机载计算机的维修性、降低维修时间,在电子设备视情维修策略上具备工程应用价值。In order to satisfy the condition-based maintenance support strategy of airborne electronic equipment based on condition monitoring and improve the maintainability of equipment,a fault diagnosis method of health monitoring management based on on on-line detection,fault prediction and assistant decision-making is proposed to support the prediction and evaluation of the health status of airborne electronic equipment.By dividing sensitive threat areas of electronic functions of airborne electronic equipment,designing special threat early warning and monitoring circuits for these areas,monitoring functional hazards,establishing reasoning monitoring model for early warning and monitoring of monitoring circuit faults,locating the early warning faults combined with assistant decision-making,and realizing electronic equipment early warning and monitoring.Intelligent fault diagnosis.Through FMEA analysis and fault injection test,the early warning circuit,reasoning model and assistant decision-making can effectively predict and locate faults,have higher fault prediction coverage,improve the maintainability of airborne computers,reduce maintenance time,and have engineering application value in electronic equipment maintenance strategy.

关 键 词：机载计算机 健康管理 故障预测 视情维修 

分 类 号：V434[航空宇航科学与技术—航空宇航推进理论与工程]