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Noise smoothing for structural vibration test signals using an improved wavelet thresholding technique.

Yi TH, Li HN, Zhao XY - Sensors (Basel) (2012)

Bottom Line: In structural vibration tests, one of the main factors which disturb the reliability and accuracy of the results are the noise signals encountered.To overcome this deficiency, this paper presents a discrete wavelet transform (DWT) approach to denoise the measured signals.The procedure is validated by using four benchmarks signals with three degrees of degradation as well as a real measured signal obtained from a three-story reinforced concrete scale model shaking table experiment.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Infrastructure Engineering, State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116023, China. yth@dlut.edu.cn

ABSTRACT
In structural vibration tests, one of the main factors which disturb the reliability and accuracy of the results are the noise signals encountered. To overcome this deficiency, this paper presents a discrete wavelet transform (DWT) approach to denoise the measured signals. The denoising performance of DWT is discussed by several processing parameters, including the type of wavelet, decomposition level, thresholding method, and threshold selection rules. To overcome the disadvantages of the traditional hard- and soft-thresholding methods, an improved thresholding technique called the sigmoid function-based thresholding scheme is presented. The procedure is validated by using four benchmarks signals with three degrees of degradation as well as a real measured signal obtained from a three-story reinforced concrete scale model shaking table experiment. The performance of the proposed method is evaluated by computing the signal-to-noise ratio (SNR) and the root-mean-square error (RMSE) after denoising. Results reveal that the proposed method offers superior performance than the traditional methods no matter whether the signals have heavy or light noises embedded.

No MeSH data available.


Sketch map of the db4 wavelet.
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f2-sensors-12-11205: Sketch map of the db4 wavelet.

Mentions: Since a quantitative criterion for selecting the attenuation factor is not available, in this paper we restricted ourselves to the Daubechies wavelet by trial and error. In all our experiments listed below, the Daubechies 4 (db4) wavelet was found to perform better in preserving fine signal details. As shown in Figure 2, the compact spatial support of db4 wavelet with four vanishing moments can provide better frequency localization and approximation and hence lead to good performance.


Noise smoothing for structural vibration test signals using an improved wavelet thresholding technique.

Yi TH, Li HN, Zhao XY - Sensors (Basel) (2012)

Sketch map of the db4 wavelet.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472880&req=5

f2-sensors-12-11205: Sketch map of the db4 wavelet.
Mentions: Since a quantitative criterion for selecting the attenuation factor is not available, in this paper we restricted ourselves to the Daubechies wavelet by trial and error. In all our experiments listed below, the Daubechies 4 (db4) wavelet was found to perform better in preserving fine signal details. As shown in Figure 2, the compact spatial support of db4 wavelet with four vanishing moments can provide better frequency localization and approximation and hence lead to good performance.

Bottom Line: In structural vibration tests, one of the main factors which disturb the reliability and accuracy of the results are the noise signals encountered.To overcome this deficiency, this paper presents a discrete wavelet transform (DWT) approach to denoise the measured signals.The procedure is validated by using four benchmarks signals with three degrees of degradation as well as a real measured signal obtained from a three-story reinforced concrete scale model shaking table experiment.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Infrastructure Engineering, State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116023, China. yth@dlut.edu.cn

ABSTRACT
In structural vibration tests, one of the main factors which disturb the reliability and accuracy of the results are the noise signals encountered. To overcome this deficiency, this paper presents a discrete wavelet transform (DWT) approach to denoise the measured signals. The denoising performance of DWT is discussed by several processing parameters, including the type of wavelet, decomposition level, thresholding method, and threshold selection rules. To overcome the disadvantages of the traditional hard- and soft-thresholding methods, an improved thresholding technique called the sigmoid function-based thresholding scheme is presented. The procedure is validated by using four benchmarks signals with three degrees of degradation as well as a real measured signal obtained from a three-story reinforced concrete scale model shaking table experiment. The performance of the proposed method is evaluated by computing the signal-to-noise ratio (SNR) and the root-mean-square error (RMSE) after denoising. Results reveal that the proposed method offers superior performance than the traditional methods no matter whether the signals have heavy or light noises embedded.

No MeSH data available.