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Denoising of structural health monitoring data: method and coding

 Denoising of structural health monitoring data: method and coding
Author(s): , , , , ORCID
Presented at IABSE Congress: Structural Engineering for Future Societal Needs, Ghent, Belgium, 22-24 September 2021, published in , pp. 504-510
DOI: 10.2749/ghent.2021.0504
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Numerous denoising approaches have already been presented to handle the noise in measured data of structural health monitoring systems. However, the performances and features of these existing meth...
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Bibliographic Details

Author(s): (Department of Bridge Engineering, Tongji University, Shanghai 200092, China)
(Department of Bridge Engineering, Tongji University, Shanghai 200092, China)
(Research Institute of Highway Ministry of Transport, Beijing 100088, China)
(Research Institute of Highway Ministry of Transport, Beijing 100088, China)
ORCID (State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌)
Medium: conference paper
Language(s): English
Conference: IABSE Congress: Structural Engineering for Future Societal Needs, Ghent, Belgium, 22-24 September 2021
Published in:
Page(s): 504-510 Total no. of pages: 7
Page(s): 504-510
Total no. of pages: 7
DOI: 10.2749/ghent.2021.0504
Abstract:

Numerous denoising approaches have already been presented to handle the noise in measured data of structural health monitoring systems. However, the performances and features of these existing methods applied in real data-set are not clear enough yet, where the noise is not known in advance. Therefore, based on the measured structural response data from a tied-arch bridge in China, six common data denoising methods are selected for a comparative study. The denoising effects are evaluated based on spectrums. Conclusions on the applicable situations and robustness of involved methods are given. A corresponding program is also developed. This study can provide references for applying the denoising methods in real structural health monitoring system data-set.

Keywords:
noise spectrum analysis denoising data polishing structural health monitoring(SHM)
Copyright: © 2021 International Association for Bridge and Structural Engineering (IABSE)
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