基于自适应奇异值分解的行星齿轮箱故障诊断方法

秦毅 1,2,张清亮 1,2,赵月 1,2

振动与冲击 ›› 2018, Vol. 37 ›› Issue (17) : 122-127.

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振动与冲击 ›› 2018, Vol. 37 ›› Issue (17) : 122-127.
论文

基于自适应奇异值分解的行星齿轮箱故障诊断方法

  • 秦毅 1,2 , 张清亮 1,2,赵月 1,2
作者信息 +

Fault diagnosis method for planetary gearboxes based on adaptive SVD

  • QIN Yi 1, 2  ZHANG Qingliang 1, 2  ZHAO Yue 1, 2
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文章历史 +

摘要

行星齿轮箱振动信号中的故障特征通常淹没在噪声信号中,因此有必要研究如何提取这些微弱故障特征。针对传统奇异值分解特征提取方法中不能自动选择有效奇异值数目的问题,提出了一种基于自适应奇异值分解的行星齿轮箱故障诊断方法。首先根据一定的条件,通过该方法选择几个不同的有效奇异值数目并得到几组不同的重构信号;再根据这些重构信号的偏态绝对值,自动选择最佳的重构信号;最后进行包络分析,得到故障信号的包络谱。仿真和实验对比结果表明,此方法相比于传统的奇异值分解特征提取方法,能够更好地在消除噪声和提取行星齿轮箱振动信号中的微弱故障特征。

Abstract

Since fault features in planetary gearbox vibration signals are usually submerged in noise signals,it is necessary to study how to extract these weak fault features. Aiming at the problem of traditional feature extraction method based on the singular value decomposition (SVD) being not able to automatically select the amount of effective singular values,a new fault diagnosis method for planetary gearboxes based on adaptive SVD was proposed. Firstly,according to a certain condition,several different amounts of effective singular values were selected with the proposed method to get several reconstructed signals. Secondly,the optimal reconstructed signal was automatically chosen according to the skew absolute values of these reconstructed signals. At last,the envelope analysis was done for the optimal reconstructed signal to acquire the envelope spectrum of the fault signal. The contrastive results between simulation and tests showed that compared to the traditional feature extraction method based on SVD,the proposed method can better de-noise and extract weak fault features in planetary gearbox vibration signals.

关键词

行星齿轮箱 / 振动信号 / 自适应奇异值分解 / 包络谱 / 降噪

Key words

 planetary gearbox / vibration signal / adaptive / singular value decomposition (SVD) / envelope spectrum / de-noising

引用本文

导出引用
秦毅 1,2,张清亮 1,2,赵月 1,2. 基于自适应奇异值分解的行星齿轮箱故障诊断方法[J]. 振动与冲击, 2018, 37(17): 122-127
QIN Yi 1, 2 ZHANG Qingliang 1, 2 ZHAO Yue 1, 2. Fault diagnosis method for planetary gearboxes based on adaptive SVD[J]. Journal of Vibration and Shock, 2018, 37(17): 122-127

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