Hybrid CEEMDAN-WTD denoising framework for stress sensor signals in bridge erection machines

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Liu, Jiajing and Zhang, Zhezheng and Fang, Weili; Moreno-Rangel, Alejandro and Kumar, Bimal, eds. (2025) Hybrid CEEMDAN-WTD denoising framework for stress sensor signals in bridge erection machines. In: EG-ICE 2025. University of Strathclyde Publishing, GBR, pp. 49-56. ISBN 9781914241826 (https://doi.org/10.17868/strath.00093248)

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Abstract

Bridge erection machines play a vital role in modern bridge construction, but structural failures resulting from inaccurate stress monitoring can lead to serious accidents. Vibrating wire strain gauges (VWSGs), which are sensitive to electromagnetic interference (EMI) in construction environments, require efficient denoising methods. To address this challenge, we propose a hybrid denoising approach that combines Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Wavelet Threshold Denoising (WTD). CEEMDAN decomposes the signal into intrinsic mode functions (IMFs), and through correlation analysis, noise-dominant IMFs are identified and denoised using WTD, while signal-dominant IMFs are left unprocessed to preserve crucial features. We validate the proposed method using field data from the Zhangjinggao Yangtze River Bridge mid-approach project. The results show effective noise suppression while retaining essential signal characteristics, providing a practical solution for monitoring systems in bridge erection machines.

  • Item type:Book Section
    ID code:93248
    Dates:
    Date
    Event
    1 July 2025
    Published
    9 June 2025
    Accepted
    Subjects:Fine Arts > Architecture
    Department:Faculty of Engineering > Architecture
    Depositing user: Pure Administrator
    Date deposited:27 Jun 2025 10:35
    Last modified:01 Aug 2026 00:16
    URI:https://strathprints.strath.ac.uk/id/eprint/93248
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