Self-Adaptive Wavelet Based on Parametric Equation in Manufacturing Engineering

Yong Jiang; Ya Ping Wang; Dong Mei Zhao

doi:10.4028/www.scientific.net/AMR.323.176

Paper Titles

An Electronic Components Screening Quality Control Method
p.157

Fuzzy PID Temperature Control in Manufacturing Engineering
p.162

Research on Management Information System of the Logistics Supply Chain of Liaoning Agricultural and Mechanical Products
p.167

Research and Design of Data-Interpreting Expert System for Geographical Prospecting of Dike Hazard
p.172

Self-Adaptive Wavelet Based on Parametric Equation in Manufacturing Engineering
p.176

Antecedence of Partnership Formation between Buyer and Supplier in Manufacturing Engineering Based on Matching Theory
p.181

A Research on Rating System of Green Construction
p.186

Research Summary of Re-Manufacturing Logistics System in China
p.192

Strategic Research to Build the Competitive Advantage of Software and Service Outsourcing Manufacturing Industry in ChongQing
p.197

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 323Self-Adaptive Wavelet Based on Parametric Equation...

Self-Adaptive Wavelet Based on Parametric Equation in Manufacturing Engineering

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.

You might also be interested in these eBooks

Innovation Manufacturing and Engineering Management

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 323)

Pages:

176-180

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.323.176

Citation:

Cite this paper

Online since:

August 2011

Authors:

Yong Jiang, Ya Ping Wang, Dong Mei Zhao

Keywords:

Manufacturing Engineering, Parameter Wavelet, Self-Adaptive Wavelet, Wavelet Noise Reduction, White Noise Detection

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Pan Quan, Meng Jinli, Zhang Lei. Wavelet Filtering Method and Its Application. Journal of Electronics & Information Technology. 2007, 29(1): 236-240.

Google Scholar

[2] Hehong Z, Tewfik A H. Parametrization of Compactly Supported Orthonrmal Wavelets. IEEE Trans. On Signal Processing, 1993, 41(3): 1428~1531.

DOI: 10.1109/78.205749

Google Scholar

[3] Zhao Xuezhi, Ye Bangyan, Chen Tongjian. Parametric Equation of Wavelet Bases without Analytic Equation. Journal of Vibration Engineering. 2004, 17(1): 16~19.

Google Scholar

[4] Baas N J, Taylor D P. Matched Filter Bounds for Wireless Communication over Rayleigh Fading Dispersive Channels. IEEE Transactions on Communications, 2001, 49(9): 1525-1528.

DOI: 10.1109/26.950339

Google Scholar

[5] Cai Tie, Zhu Jie. Adaptive Selection of Optimal Decomposition Level in Threshold Denoising Algorithm Based on Wavelet. Control and Choice, 2006, 21(2): 217-220.

Google Scholar

[6] Box Gep, Jenknsgm, Rensel G C. Time Series Analysis Forecasting and Control. Englewood C lifs, N J, Prentice Hall, (1994).

Google Scholar

[7] Leontitsis A, Bountis T. An Adaptive Way for Improving Noise Reduction Using Local Geometric Projection. Chaos, 2004, 14(1): 106-110.

DOI: 10.1063/1.1622354

Google Scholar