基于 DRSN 与电压幅值分析的航空 HVDC 系统逆变器故障诊断

Zhanjun Huang, Xin Dong, Muyu Lu, Ruitao Zhang, Zhaoyang Yan, An Zhang

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

The fault diagnosis of the airborne 270 V high-voltage direct current(HVDC)system has always been a difficult problem in the field of avionics. Therefore,a fault module identification algorithm based on deep residual contraction network(DRSN)and a fault component localization algorithm based on line voltage amplitude analysis have been proposed. Firstly,the total current of the system is collected,and the difference is standardized to obtain characteristic data. Based on the feature data,the Flatten layer is used to improve the original DRSN structure,so as to improve the algorithm recognition accuracy for fault modules. After determining the fault of the system inverter module,the fault phase is determined using the ratio of the two phase line-voltages,and then the fault device is determined using the average line-voltage model. Compared to existing methods,the proposed method only uses one current sensor and two voltage sensors to achieve system fault diagnosis,meeting the weight limitation requirements of aircraft. The experiment proves that the proposed method has good practicality in identifying fault modules and locating fault components with an accuracy of over 97%.

投稿的翻译标题Fault diagnosis of inverter of aviation HVDC sysytem based on DRSN and voltage amplitude analysis
源语言繁体中文
文章编号328685
期刊Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica
45
3
DOI
出版状态已出版 - 15 2月 2024

关键词

  • 270 V HVDC system
  • deep residual shrinkage network
  • fault diagnosis
  • fault module identification
  • line voltage amplitude analysis

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