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Sensors 2012, 12(8), 11205-11220; doi:10.3390/s120811205
Article

Noise Smoothing for Structural Vibration Test Signals Using an Improved Wavelet Thresholding Technique

1,* , 1
 and 2
Received: 11 June 2012 / Revised: 6 August 2012 / Accepted: 6 August 2012 / Published: 10 August 2012
(This article belongs to the Section Physical Sensors)
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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.
Keywords: vibration testing; wavelet transform (WT); denoise; wavelet thresholding; sigmoid function vibration testing; wavelet transform (WT); denoise; wavelet thresholding; sigmoid function
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Yi, T.-H.; Li, H.-N.; Zhao, X.-Y. Noise Smoothing for Structural Vibration Test Signals Using an Improved Wavelet Thresholding Technique. Sensors 2012, 12, 11205-11220.

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