Issue |
JNWPU
Volume 41, Number 3, June 2023
|
|
---|---|---|
Page(s) | 546 - 556 | |
DOI | https://doi.org/10.1051/jnwpu/20234130546 | |
Published online | 01 August 2023 |
AFDX network equipment fault diagnosis technology
AFDX网络设备故障诊断技术
1
General Pneumatic Department, Shenyang Aircraft Design and Research Institute, Shenyang 110034, China
2
Integrated Avionics Department, Shenyang Aircraft Design and Research Institute, Shenyang 110034, China
3
School of Software, Northwestern Polytechnical University, Xi'an 710072, China
4
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China
Received:
28
July
2022
This paper focuses on the network equipment fault monitoring and diagnosis software, and studies the fault diagnosis of the monitored AFDX network based on the network algorithm. Firstly, the range fault characteristic parameters are designed to identify the fault type, and the correlation between the detection results and the fault characteristic parameters at each location can be obtained. Secondly, the data storage management scheme of the first level filtering and the second level caching mechanism is designed for the data collected in the detection. Then, according to the designed fault classification, fault diagnosis methods are given respectively, and the occasional anomalies are identified and suppressed. Finally, the network fault diagnosis verification module is designed, and the experimental verification is carried out from the perspectives of real-time and concurrency. The verification results prove the effectiveness of the method.
摘要
AFDX网络作为机载主干通信网络,如果出现故障,将影响整个航电系统的功能。AFDX网络设备故障诊断对于机载通信的稳定运行和航空子系统故障管理具有重要意义。聚焦网络设备故障诊断技术,研究了一套基于网络演算法的AFDX网络设备故障诊断技术。通过设计故障特征参数标识故障类型,给出检测结果和故障特征参数的关联关系;使用被动式采集的方式对关键元器件、通信过程以及设备性能进行状态检测;针对所收集的检测数据,分别给出故障诊断方法并对偶发性异常进行识别和抑制;设计网络故障诊断测试用例,从实时性和并发性2个角度进行测试验证,测试用例的通过率达到98%,且未发生致命、严重级别的BUG,较小级别的BUG不超过5个且均已修复,验证结果证明了方法的有效性。
Key words: AFDX network / network equipment / fault diagnosis / network monitoring
关键字 : AFDX网络 / 网络设备 / 故障诊断 / 网络监控
© 2023 Journal of Northwestern Polytechnical University. All rights reserved.
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