AFDX network equipment fault diagnosis technology

Q3 Engineering 西北工业大学学报 Pub Date : 2023-06-01 DOI:10.1051/jnwpu/20234130546
Lei Hu, Yang Liu, Q. Guo, Yu Shi, Chunyan Ma, Jian-dong Zhang, Tao Zhang
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Abstract

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.
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AFDX网络设备故障诊断技术
本文重点研究了网络设备故障监测与诊断软件,并研究了基于网络算法的AFDX网络故障诊断。首先,设计测距故障特征参数来识别故障类型,并可以获得每个位置的检测结果与故障特征参数之间的相关性。其次,针对检测中采集到的数据,设计了一级过滤和二级缓存机制的数据存储管理方案。然后,根据设计的故障分类,分别给出了故障诊断方法,并对偶尔出现的异常进行了识别和抑制。最后,设计了网络故障诊断验证模块,并从实时性和并发性角度进行了实验验证。验证结果证明了该方法的有效性。
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来源期刊
西北工业大学学报
西北工业大学学报 Engineering-Engineering (all)
CiteScore
1.30
自引率
0.00%
发文量
6201
审稿时长
12 weeks
期刊介绍:
期刊最新文献
Research on the safe separation corridor of the combined aircraft and its generation method Cracking mechanism analysis and experimental verification of encapsulated module under high low temperature cycle considering residual stress AFDX network equipment fault diagnosis technology MUSIC algorithm based on eigenvalue clustering Target recognition algorithm based on HRRP time-spectrogram feature and multi-scale asymmetric convolutional neural network
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