Volume 39, Number 1, February 2021
|Page(s)||71 - 76|
|Published online||09 April 2021|
Research on typical fault classification method of DC-DC converter
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China
2 Science and Technology on Avionics Integration Laboratory, China Institute of Aeronautical Radio Electronics, Shanghai 200233, China
3 Xi'an Modern Control Technology Research Institute, Xi'an 710065, China
DC-DC converter is the core component of power conversion module of integrated modular avionics. Condition monitoring and fault diagnosis of DC-DC converter can effectively improve the reliability of avionics equipment, reduce the maintenance cost and greatly improve the use efficiency of aircraft. In this paper, firstly, a typical DC-DC converter model based on SEPIC topology is designed in PSPICE environment, and the failure modes of DC-DC converter are analyzed. Secondly, the typical fault types of DC-DC converter are simulated, and the corresponding original data are obtained through simulation. Finally, the processing framework including data preprocessing, feature extraction and selection, and multi model fusion is used to do fault classification of the DC-DC converter. The fault diagnosis of the converter is simulated. Simulation results show the effectiveness of the proposed method.
Key words: DC-DC converter / failure modes / feature extraction / fault classification / multi model fusion / simulation / SEPIC topology
关键字 : DC-DC变换器 / 特征提取 / 故障分类 / 多模型融合
© 2021 Journal of Northwestern Polytechnical University. All rights reserved.
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