Adaptive denoising method of bridge vibration signal based on EWT-noise aided analysis theory
LUO Yeke1, CHEN Yonggao1, LI Shengcai2
1.Department of Civil Engineering and Architecture， Zhejiang Industry Polytechnic College， Shaoxing 312000， China;
2.School of Civil Engineering， Huaqiao University， Quanzhou 362000， China
Abstract：The response of bridge structure under environmental excitation is susceptible to noise interference, which leads to the inability to effectively distinguish the characteristic components contained in the signal. Aiming at the limitations of the existing noise reduction methods, the noise aided analysis theory is introduced into the empirical wavelet transform (EWT) for improvement. Firstly, the key parameters of improved EWT are adaptively determined based on energy criterion and residual frequency domain probability density curve characteristics. Secondly, according to the product of energy density and average period and JS divergence, the screening coefficient is constructed to realize the feature selection of signal components. Finally, the signal component is integrated by frequency domain error index, and the iterative signal component is reconstructed to achieve noise reduction effect. In order to verify the noise reduction ability of the improved EWT, the simulation signal and the monitoring signal of a cable-stayed bridge are taken as the research objects. The noise reduction performance of each method is compared through the time domain, frequency domain and time-frequency domain graphics of each noise reduction index. The results show that the improved EWT has stronger noise reduction ability. It can effectively extract the characteristic component while suppressing the noise, avoiding the data redundancy caused by excessive segmentation and overall integration, and can be used for the dynamic response analysis of the actual bridge.
Key words: Bridge Structure；Denoise Method；Empirical Wavelet Transform (EWT)；Noise-Assisted Analysis
罗烨钶1，陈永高1，李升才2. 基于经验小波变换-噪声辅助分析的桥梁信号降噪方法[J]. 振动与冲击, 2022, 41(21): 246-256.
LUO Yeke1, CHEN Yonggao1, LI Shengcai2. Adaptive denoising method of bridge vibration signal based on EWT-noise aided analysis theory. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(21): 246-256.
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