An Improved Wavelet Threshold De-Noising Data Processing Method Research in Deformation Monitoring

Wei Li; Xu Wang

doi:10.4028/www.scientific.net/AMM.90-93.2858

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 90-93An Improved Wavelet Threshold De-Noising Data...

An Improved Wavelet Threshold De-Noising Data Processing Method Research in Deformation Monitoring

Abstract:

Due to the soft and hard threshold function exist shortcomings. This will reduce the performance in wavelet de-noising. in order to solve this problem，This article proposes Modulus square approach. the new approach avoids the discontinuity of the hard threshold function and also decreases the fixed bias between the estimated wavelet coefficients and the wavelet coefficients of the soft-threshold method．Simulation results show that SNR and MSE are better than simply using soft and hard threshold，having good de-noising effect in Deformation Monitoring.

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Periodical:

Applied Mechanics and Materials (Volumes 90-93)

Pages:

2858-2863

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.90-93.2858

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Online since:

September 2011

Authors:

Wei Li, Xu Wang

Keywords:

Deformation Monitoring, Modulus Squared Model, Threshold De-Noising, Wavelet Analysis

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