Faculty of Infrastructure Engineering, State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116023, China.
Sensors (Basel). 2012;12(8):11205-20. doi: 10.3390/s120811205. Epub 2012 Aug 10.
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.
在结构振动测试中，干扰结果可靠性和准确性的主要因素之一是遇到的噪声信号。为了克服这一缺陷，本文提出了一种离散小波变换（DWT）方法来对测量信号进行去噪。通过几个处理参数，包括小波类型、分解层次、阈值方法和阈值选择规则，讨论了 DWT 的去噪性能。为了克服传统硬阈值和软阈值方法的缺点，提出了一种改进的阈值技术，称为基于 sigmoid 函数的阈值方案。该程序通过使用四个基准信号（退化程度分别为三级）以及从三层钢筋混凝土比例模型振动台实验中获得的真实测量信号进行了验证。通过计算去噪后的信噪比（SNR）和均方根误差（RMSE）来评估所提出方法的性能。结果表明，无论信号中嵌入的噪声是重还是轻，所提出的方法都比传统方法具有更好的性能。
