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A Morphology Filter-Assisted Extreme-Point Symmetric Mode Decomposition (MF-ESMD) Denoising Method for Bridge Dynamic Deflection Based on Ground-Based Microwave Interferometry

机译:基于地面微波干涉法的桥梁动态偏转的形态滤波辅助极点对称模式分解(MF-ESMD)去噪方法

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Bridge dynamic deflection is an important indicator of structure safety detection. Ground-based microwave interferometry is widely used in bridge dynamic deflection monitoring because it has the advantages of noncontact measurement and high precision. However, due to the influences of various factors, there are many noises in the obtained dynamic deflection of bridges obtained by ground-based microwave interferometry. To reduce the impacts of noise for bridge dynamic deflection obtained with ground-based microwave interferometry, this paper proposes a morphology filter-assisted extreme-point symmetric mode decomposition (MF-ESMD) for the signal denoising of bridge dynamic deflection obtained by ground-based microwave interferometry. First, the original bridge dynamic deflection obtained with ground-based microwave interferometry was decomposed to obtain a series of intrinsic mode functions (IMFs) with the ESMD method. Second, the noise-dominant IMFs were removed according to Spearman’s rho algorithm, and the other decomposed IMFs were reconstructed as a new signal. Finally, the residual noises in the reconstructed signal were further eliminated using the morphological filter method. The results of both the simulated and on-site experiments showed that the proposed MF-ESMD method had a powerful signal denoising ability.
机译:桥梁动态偏转是结构安全检测的重要指标。基于地基的微波干涉测量法广泛用于桥梁动态偏转监测,因为它具有非接触式测量和高精度的优点。然而,由于各种因素的影响,通过地基微波干涉测量法获得的桥梁的动态偏转存在许多噪声。为了减少用地面微波干涉测量获得的桥梁动态偏转的影响,本文提出了一种通过地面基于基于桥接动态偏转的信号去噪微波干涉测量。首先,用基于地基微波干涉测量法获得的原始桥接动态偏转被分解以获得具有ESMD方法的一系列内在模式功能(IMF)。其次,根据Spearman的rho算法除去噪声主导IMF,并将其它分解的IMF重建为新信号。最后,使用形态过滤方法进一步消除重建信号中的残余噪声。模拟和现场实验的结果表明,所提出的MF-ESMD方法具有强大的信号去噪能力。

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