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作 者:黄湛钧 胡康 张安[1] 董林林 陈骁骅 HUANG Zhanjun;HU Kang;ZHANG An;DONG Linlin;CHEN Xiaohua(School of Aeronautics,Northwestern Polytechnical University,Xi'an,Shaanxi 718400,China)
出 处:《河北工业大学学报》2023年第6期14-23,共10页Journal of Hebei University of Technology
基 金:国家自然科学基金(62003274);陕西省青年项目(5113220040);中央高校基本科研业务费专项资金(G2020KY05110)。
摘 要:工业测量中的数据丢失会导致被测信号序列采样数据的缺失,进一步使得重构波形的局部特征与实际信号出现差异。该问题在稀疏数据点构成的信号序列中尤为严重,非完整信号序列将为航空电源系统的故障诊断带来挑战。针对该问题,提出一种基于电流宏观波形相似性度量的时域故障诊断方法。首先,监测航空电源系统三相输出电流并进行归一化处理;其次,根据正弦电流波形特征进行信号序列重构以消除三相相位差异;再次,采用动态时间规整算法对数据缺失的非等长信号序列进行补齐并使三相序列数据元素相匹配;继次,基于序列匹配关系构建电流波形绝对和相对相似度作为诊断变量;最后,K-近邻算法被用于故障模式的识别。经过验证与比较分析,所提方法能够基于数据缺失的稀疏信号序列,准确实现航空电源系统的开路故障诊断。The data missing in industrial measurement will lead to the loss of sampling data of the signal sequence,which further makes the characteristics of the reconstructed waveform different from the actual signal.This problem is particularly serious in signal sequences composed of sparse data points,where incomplete signal sequences can pose challenges for fault diagnosis of aviation power system.To address this problem,a time-domain fault diagnosis method based on the similarity measurement of current waveform is proposed.Firstly,the three-phase current is monitored and normalized.Secondly,the signal sequence reconstruction is carried out according to the sinusoidal current waveform characteristic to eliminate the phase difference.Thirdly,the dynamic time wrapping is used to complete the missing nonisometric signal sequences and match the data elements of different series.Next,the absolute and relative similarity of the current waveform is obtained as diagnostic variables based on the sequence matching relationship.Finally,the Knearest neighbor is used for fault mode identification.It is verified that the proposed method can accurately realize the open-circuit fault diagnosis of aviation power system based on the sparse signal sequence with missing data.
关 键 词:航空电源系统 故障诊断 数据缺失 波形相似度 动态时间规整
分 类 号:V242.2[航空宇航科学与技术—飞行器设计]
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