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

Abstract 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 characterist...

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Autores principales:	Kai Wei, Xuwen Jing, Bingqiang Li, Chao Kang, Zhenhuan Dou, Jinfeng Liu, Yu Chen, Hainan Zheng
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/42845213bbb2484a8431847921f3fd0a
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spelling	oai:doaj.org-article:42845213bbb2484a8431847921f3fd0a2021-12-02T15:10:39ZA combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery10.1038/s41598-021-96343-22045-2322https://doaj.org/article/42845213bbb2484a8431847921f3fd0a2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96343-2https://doaj.org/toc/2045-2322Abstract 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, Rényi 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.Kai WeiXuwen JingBingqiang LiChao KangZhenhuan DouJinfeng LiuYu ChenHainan ZhengNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kai Wei Xuwen Jing Bingqiang Li Chao Kang Zhenhuan Dou Jinfeng Liu Yu Chen Hainan Zheng A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery
description	Abstract 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, Rényi 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.
format	article
author	Kai Wei Xuwen Jing Bingqiang Li Chao Kang Zhenhuan Dou Jinfeng Liu Yu Chen Hainan Zheng
author_facet	Kai Wei Xuwen Jing Bingqiang Li Chao Kang Zhenhuan Dou Jinfeng Liu Yu Chen Hainan Zheng
author_sort	Kai Wei
title	A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery
title_short	A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery
title_full	A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery
title_fullStr	A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery
title_full_unstemmed	A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery
title_sort	combined generalized warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/42845213bbb2484a8431847921f3fd0a
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A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery

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