Open AccessAn Adaptive Filtering Method for Bridge Vibration Signals Based on Improved CEEMDAN and Multi-Scale Permutation Entropy
Author(s) -
Dawei He,
Boxin Wang,
Xinliang Gao,
Xia Wang
Publication year - 2021
Publication title -
environmental and earth sciences research journal
Language(s) - English
Resource type - Journals
eISSN - 2369-5676
pISSN - 2369-5668
DOI - 10.18280/eesrj.080404
Subject(s) - noise reduction , algorithm , vibration , entropy (arrow of time) , white noise , hilbert–huang transform , computer science , noise (video) , control theory (sociology) , mathematics , pattern recognition (psychology) , artificial intelligence , acoustics , statistics , physics , control (management) , quantum mechanics , image (mathematics)
Aiming at the serious noise of bridge vibration signals in complex environment, this paper proposed an adaptive filtering and denoising optimization method for bridge structural health monitoring. The method took CEEMDAN algorithm as the core, during the step-by-step decomposition of original signals, white noise with opposite signs was added in each stage, meanwhile multi-scale permutation entropy (MPE) was introduced to analyze the mean entropy of each intrinsic mode function (IMF) at different scales, and components with serious noise were eliminated to complete the first filtering; then, in order to optimize the remaining IMFs for signal reconstruction and ensuring the smoothness and similarity of filtering, an optimized reconstruction model was established to complete the second filtering. Compared with the CEEMDAN method, the proposed method could solve the problems of mode mixing and endpoint effect with good completeness, orthogonality, and signal-to-noise ratio. At last, the advantages and application value of the proposed method were verified again by the vibration signal analysis of a real long-span bridge structure.