基于Schavemaker模型和小波分析的航空EWIS故障电弧检测技术  

Fault Arc Detection Technology for Aviation EWIS Based on Schavemaker Model and Wavelet Analysis

作　　者：张志亮 王希彬 贾临生 戴洪德 Zhang Zhiliang;Wang Xibin;Jia Linsheng;Dai Hongde(School of Basic Science for Aviation,Naval Aviation University,Yantai 264001,China;No.32151 Unit of PLA,Xingtai 054000,China)

机构地区：[1]海军航空大学航空基础学院,山东烟台264001 [2]中国人民解放军32151部队,河北邢台054000

出　　处：《兵工自动化》2024年第9期49-54,共6页Ordnance Industry Automation

基　　金：国防科技项目基金(F062102009);山东省高等学校青年创新团队(2020KJN003)。

摘　　要：针对航空线路系统故障电弧检测问题,在分析故障电弧的成因和基本特征的基础上,设计一种基于小波分析的故障电弧检测算法。分析基于Schavemaker电弧模型的交流串联故障电弧发生电路,采用sym5小波对故障电弧电流数据进行分解,提取出电流的高频部分,并提出基于高频分量d_3标准差的故障电弧检测方法,基于Simulink对该算法进行仿真验证。仿真结果表明:该方法比传统的小波分解后直接设定阈值检测故障电弧方法区分度高,能快速准确地确定故障电弧的存在,为工程实践提供有益参考。Aiming at the problem of fault arc detection in aviation line system,based on the analysis of the causes and basic characteristics of fault arc,a fault arc detection algorithm based on wavelet analysis is designed.This paper analyzes the AC series arc fault circuit based on Schavemaker arc model,uses sym5 wavelet to decompose the fault arc current data,extracts the high frequency part of the current,and proposes a fault arc detection method based on the d3 standard deviation of the high frequency component,and simulates the algorithm based on Simulink.The simulation results show that the proposed method has a higher degree of discrimination than the traditional method of directly setting the threshold after wavelet decomposition,and can quickly and accurately determine the existence of fault arc,which provides a useful reference for engineering practice.

关 键 词：故障电弧 故障电弧检测 电弧模型 小波分析 波动率 

分 类 号：V242[航空宇航科学与技术—飞行器设计]