Denoising Method for Deformation Monitoring Data Based on ICEEMD⁃ICA and MDP Principle

被引：0
|
作者：
Xu C. [1 ]
Fan Q. [2 ]
机构：
[1] Geography and Ocean College, Minjiang University, Fuzhou
[2] College of Civil Engineering, Fuzhou University, Fuzhou
来源：
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2021年 / 46卷 / 11期
基金：
中国国家自然科学基金;
关键词：
Denoising for deformation monitoring data; Improved complete ensemble empirical mode decomposition(ICEEMD); Independent component analysis(ICA); Minimal distortion principle; Twice virtual noise;
D O I：
10.13203/j.whugis20190174
中图分类号：
学科分类号：
摘要：
Objectives: Considering the inaccurate separation of signal and noise of empirical mode decomposition (EMD) method and the uncertainty of independent component analysis (ICA), a new method for denoising deformation data with improved complete ensemble empirical mode decomposition (ICEEMD), independent component analysis (ICA) and minimal distortion principle (MDP) is proposed. Methods: Firstly, ICEEMD method is used to decompose the deformation monitoring data effectively, and the virtual noise signal is constructed. Secondly, ICEEMD decomposition of virtual noise is carried out to extract twice virtual noise signal which is closer to real noise. The input observation channel is composed of twice virtual noise and original deformation data and processed by ICA. Then, by calculating the correlation coefficient between the independent components and the input signal after ICA processing, the sorting uncertainty and phase uncertainty of independent components can be solved. Finally, the MDP criterion is used to effectively solve the amplitude uncertainty of independent components. Results: Through the detailed analysis of noisy simulation data and actual bridge GNSS deformation monitoring data, the results show that the proposed method has achieved good denoising effect and can effectively improve the performance of denoising. Conclusions: It also fully verified the feasibility and effectiveness of the proposed method indenoising of deformation monitoring data. © 2021, Editorial Board of Geomatics and Information Science of Wuhan University. All right reserved.
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页码：1658 / 1665
页数：7
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