2011Advanced materials researchOpen access

Self-Adaptive Wavelet Based on Parametric Equation in Manufacturing Engineering

Yong Jiang, Ya Ping Wang, Dong Mei Zhao

Open full text 0 citations

Abstract

The paper analyzes the difference between useful signal and noise signal in dissemination characteristic inside wavelet space in manufacturing engineering, and then puts forward a search algorithm based on wavelet decorrelation white noise testing and involved with the parameters in a parametric equation. The algorithm can select wavelet transform to realize the best noise reduction effect in a self-adaptive way according to the characteristic of signal containing noise and signal to noise ratio. At last, simulation experiment and engineering application are made, and their results are compared with the decomposition result of Daubechies wavelet. It’s concluded that self-adaptive wavelet basis can more adequately separate useful information from signal.

About this research paper

What this paper is about

The paper analyzes the difference between useful signal and noise signal in dissemination characteristic inside wavelet space in manufacturing engineering, and then puts forward a search algorithm based on wavelet decorrelation white noise testing and involved with the parameters in a parametric equation. The algorithm can select wavelet transform to realize the best noise reduction effect in a self-adaptive way according to the characteristic of signal containing noise and signal to noise ratio. At last, simulation experiment and engineering application are made, and their results are compared with the decomposition result of Daubechies wavelet. It’s concluded that self-adaptive wavelet basis can more adequately separate useful information from signal.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The paper analyzes the difference between useful signal and noise signal in dissemination characteristic inside wavelet space in manufacturing engineering, and then puts forward a search algorithm based on wavelet decorrelation white noise testing and involved with the parameters in a parametric equation. The algorithm can select wavelet transform to realize the best noise reduction effect in a self-adaptive way according to the characteristic of signal containing noise and signal to noise ratio. At last, simulation experiment and engineering application are made, and their results are compared with the decomposition result of Daubechies wavelet. It’s concluded that self-adaptive wavelet basis can more adequately separate useful information from signal.

Key concepts: Wavelet, Daubechies wavelet, Wavelet packet decomposition, Second-generation wavelet transform, Decorrelation, Discrete wavelet transform, Stationary wavelet transform, Wavelet transform

Related papers

Back to paper searchBrowse research topicsOriginal source
Self-Adaptive Wavelet Based on Parametric Equation in Manufacturing Engineering — Research Paper | ScholarLens