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Wavelet de-noising with improved threshold method for bridge health monitoring

机译:改进阈值法的小波消噪用于桥梁健康监测

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In order to overcome the defects of traditional wavelet threshold method and improve the quality of bridge health monitoring signals, an improved wavelet threshold de-noising method based on the bridge deflection signals is proposed. First, the improved threshold can adaptively select different thresholds in different decomposition layers. Then, the wavelet coefficients of the bridge deflection signals are modeled to determine the statistical properties of deflection signals. Next, an improved wavelet shrinkage function is obtained based on these statistical properties. The bridge deflection signal de-noising experiments show that the actual de-noising effect is significant, and this proposed de-noising method is suitable for processing the deflection signal of the bridge monitoring system.
机译:为了克服传统小波阈值法的缺陷,提高桥梁健康监测信号的质量,提出了一种基于桥梁挠度信号的改进的小波阈值降噪方法。首先,改进的阈值可以在不同的分解层中自适应地选择不同的阈值。然后,对桥偏转信号的小波系数建模,以确定偏转信号的统计特性。接下来,基于这些统计特性获得改进的小波收缩函数。桥梁挠度信号的去噪实验表明,实际的去噪效果是显着的,所提出的去噪方法适用于桥梁监控系统的挠度信号的处理。

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