Research on typical fault classification method of DC-DC converter

• Format: Article
• Language: zho
• Published: The Northwestern Polytechnical University 2021-02-01
• Series: Xibei Gongye Daxue Xuebao
• Subjects: dc-dc converter; failure modes; feature extraction; fault classification; multi model fusion; simulation; sepic topology
• Online Access: https://www.jnwpu.org/articles/jnwpu/full_html/2021/01/jnwpu2021391p71/jnwpu2021391p71.html

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.