首页|DHSI筛选奇异值分量在齿轮故障诊断中的应用

DHSI筛选奇异值分量在齿轮故障诊断中的应用

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为有效剥离传动系统齿轮故障信号中的噪声成分,提出基于差分谐波显著指数(Differential Harmonic Significance Index,DHSI)筛选奇异值分量的齿轮故障诊断方法.该方法首先对原始信号构造Hankel矩阵,并对该矩阵进行奇异值分解,然后利用提出的一种新的奇异值突变位置判别指数,即奇异分量的差分谐波显著指数筛选奇异值的个数,并由这些奇异值分量重构信号,得到故障信号的包络谱.应用该方法分析齿轮故障仿真信号以及某型直升机传动系统并车级齿轮掉块故障信号,与基于奇异值差分谱的奇异值分量筛选结果对比表明,基于差分谐波显著指数的奇异值分量筛选能够更好地消除噪声并提取齿轮振动信号中的故障特征.
Application of DHSI Screening Singular Value Components in Gear Fault Diagnosis
In order to effectively remove the noise components in the gear transmission fault signals,a fault diagnosis method based on the differential harmonic significance index(DHSI)for screening singular value components was proposed.In this method,a Hankel matrix was constructed based on the original signal and the constructed matrix was decomposed into the singular values.Then,a new singular value mutation position discrimination index,namely the differential harmonic significance index of singular components,was proposed to screen out the number of the singular values.The signal was reconstructed based on these singular components,and the envelope spectrum of the fault signal was obtained.This method was applied to analyze gear fault simulation signal and the parallel stage gear dropout fault signal of a certain type helicopter transmission system.The comparison of the results of this method with the results of singular value component screening based on singular value difference spectrum show that the singular value component screening based on DHSI can better eliminate the noise and extract fault features in gear vibration signals.

fault diagnosisharmonic significant indexsingular value decompositionharmonic product spectrumgear transmission

杨伟新、刘飞春、唐鑫、朱如鹏

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中国航发湖南动力机械研究所 航空发动机振动技术航空科技重点实验室,湖南 株洲 412002

南京航空航天大学 机电学院,南京 210016

故障诊断 谐波显著指数 奇异值分解 谐波积频谱 齿轮传动

2024

噪声与振动控制
中国声学学会

噪声与振动控制

CSTPCD北大核心
影响因子:0.622
ISSN:1006-1355
年,卷(期):2024.44(5)