Wavelet decomposition and nonlinear prediction of nonstationary vibration signals. (March 2020)

• Record Type: Journal Article
• Authors: Fan, Xiao-bin; Zhao, Bin; Fan, Bing-xu
• Is Part Of: Noise & vibration worldwide. Volume 51:Number 3(2020)
• Page Start: 52
• Page End: 59
• Publication Date: 2020-03
• Subjects: Wavelet decomposition -- nonstationary signal -- nonlinear prediction -- vibration -- time series; Noise control -- Periodicals; Damping (Mechanics) -- Periodicals; Soundproofing -- Periodicals; Damping (Mechanics); Noise control; Soundproofing; Periodicals; 620.205
• DOI: 10.1177/0957456519900797
• Languages: English
• ISSNs: 0957-4565

Abstract

In order to overcome the shortcomings (such as the time–frequency localization and the nonstationary signal analysis ability) of the Fourier transform, time–frequency analysis has been carried out by wavelet packet decomposition and reconstruction according to the actual nonstationary vibration signal from a large equipment located in a large Steel Corporation in this article. The effect of wavelet decomposition on signal denoising and the selection of high-frequency weight coefficients for each layer on signal denoising were analyzed. The nonlinear prediction of the chaotic time series was made by global method, local method, weighted first-order local method, and maximum Lyapunov exponent prediction method correspondingly. It was found the multi-step prediction method is better than other prediction methods.