Missing measurement data recovery methods in structural health monitoring: The state, challenges and case study-Reference-Cited by-同舟云学术

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Missing measurement data recovery methods in structural health monitoring: The state, challenges and case study

Published:2024-05 Issue: Volume:231 Page:114528
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Zhang Jianwei,Huang Minshui^ORCID,Wan Neng,Deng Zhihang,He Zhongao,Luo Jin

Publisher

Elsevier BV

Reference110 articles.

1. Convolutional neural network-based data recovery method for structural health monitoring;Oh;Struct. Health. Monit.,2020

2. Bayesian modeling approach for forecast of structural stress response using structural health monitoring data;Wan;J. Struct. Eng.,2018

3. A hybrid method coupling empirical mode decomposition and a Long short-term memory network to predict missing measured signal data of SHM systems;Li;Struct. Health. Monit.,2021

4. A missing sensor measurement data reconstruction framework powered by multi-task Gaussian process regression for dam structural health monitoring systems;Li;Measurement.,2021

5. Compressive sampling-based data loss recovery for wireless sensor networks used in civil structural health monitoring;Bao;Struct. Health. Monit.,2013

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