A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery

被引：5

作者：

Wei, Kai ^{[1
]}

Jing, Xuwen ^{[1
]}

Li, Bingqiang ^{[1
]}

Kang, Chao ^{[1
]}

Dou, Zhenhuan ^{[2
]}

Liu, Jinfeng ^{[1
]}

Chen, Yu ^{[1
]}

Zheng, Hainan ^{[1
]}

机构：

[1] Jiangsu Univ Sci & Technol, Sch Mech Engn, Zhenjiang 212013, Jiangsu, Peoples R China

[2] Shaanxi Diesel Heavy Ind LTD, Xian, Peoples R China

来源：

SCIENTIFIC REPORTS | 2021年 / 11卷 / 01期

关键词：

TIME-FREQUENCY ANALYSIS; CHIRPLET TRANSFORM;

D O I：

10.1038/s41598-021-96343-2

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In recent years, considerable attention has been paid in time-frequency analysis (TFA) methods, which is an effective technology in processing the vibration signal of rotating machinery. However, TFA techniques are not sufficient to handle signals having a strong non-stationary characteristic. To overcome this drawback, taking short-time Fourier transform as a link, a TFA methods that using the generalized Warblet transform (GWT) in combination with the second order synchroextracting transform (SSET) is proposed in this study. Firstly, based on the GWT and SSET theories, this paper proposes a method combining the two TFA methods to improve the TFA concentration, named GWT-SSET. Secondly, the method is verified numerically with single-component and multi-component signals, respectively. Quantized indicators, Renyi entropy and mean relative error (MRE) are used to analyze the concentration of TFA and accuracy of instantly frequency (IF) estimation, respectively. Finally, the proposed method is applied to analyze nonstationary signals in variable speed. The numerical and experimental results illustrate the effectiveness of the GWT-SSET method.

引用

页数：12

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