APPLICATION OF SWT-AUTOCORRELATION METHOD IN GEAR WEAK FAULT DIAGNOSIS

被引：0

作者：

Zhao, Meng-yuan ^{[1
]}

Zhang, Xu-guang ^{[1
]}

Leng, Jun-fa ^{[1
]}

Jing, Shuang-xi ^{[1
]}

机构：

[1] Henan Polytech Univ, Sch Mech & Power Engn, Jiaozuo 454003, Henan, Peoples R China

来源：

PROCEEDINGS OF THE 2020 15TH SYMPOSIUM ON PIEZOELECTRCITY, ACOUSTIC WAVES AND DEVICE APPLICATIONS (SPAWDA) | 2021年

关键词：

Gear box; Weak fault feature extraction; Synchrosqueezing wavelet transform; Autocorrelation analysis;

D O I：

10.1109/SPAWDA51471.2021.9445510

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper proposes a weak fault diagnosis method of gear based on the combination of synchrosqueezing wavelet transform(SWT) and autocorrelation analysis. Firstly, the multi-component vibration signal is decomposed into several intrinsic mode functions(IMFs) by SWT, then autocorrelation analysis denoising is performed on the selected IMFs, and the envelope analysis and frequency spectrum analysis are performed on this IMFs with fault components. Simulation and experimental results show that this method can effectively extract the weak fault feature for gear fault diagnosis.

引用

页码：598 / 602

页数：5

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