Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …
smart monitoring and decision-making solutions. Near real-time and online damage …
The current development of structural health monitoring for bridges: a review
Z Deng, M Huang, N Wan, J Zhang - Buildings, 2023 - mdpi.com
The health monitoring system of a bridge is an important guarantee for the safe operation of
the bridge and has always been a research hotspot in the field of civil engineering. This …
the bridge and has always been a research hotspot in the field of civil engineering. This …
Lost data reconstruction for structural health monitoring using deep convolutional generative adversarial networks
In the application of structural health monitoring, the measured data might be temporarily or
permanently lost due to sensor fault or transmission failure. The measured data with a high …
permanently lost due to sensor fault or transmission failure. The measured data with a high …
Data driven structural dynamic response reconstruction using segment based generative adversarial networks
Reconstruction of lost responses under external loads, eg ambient and seismic loading
conditions, is important for structural health monitoring to evaluate the safety of structures …
conditions, is important for structural health monitoring to evaluate the safety of structures …
[HTML][HTML] An approach towards missing data management using improved GRNN-SGTM ensemble method
The paper considers missing data management task in smart systems. The main strategies
of missing data management in handling missing data are analyzed. A prediction method for …
of missing data management in handling missing data are analyzed. A prediction method for …
Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring
H Jiang, C Wan, K Yang, Y Ding… - Structural Health …, 2022 - journals.sagepub.com
Wireless sensors are the key components of structural health monitoring systems. During the
signal transmission, sensor failure is inevitable, among which, data loss is the most common …
signal transmission, sensor failure is inevitable, among which, data loss is the most common …
A novel method for the recovery of continuous missing data using multivariate variational mode decomposition and fully convolutional networks
Q Tang, Y Jiang, J Xin, G Liao, J Zhou, X Yang - Measurement, 2023 - Elsevier
The sensor failure is the frequently-occurring event in engineering activities related to the
measurement, which could yield a serious problem of continuous data loss. This special …
measurement, which could yield a serious problem of continuous data loss. This special …
Reconstruction of structural long-term acceleration response based on BiLSTM networks
Reconstructing lost dynamic responses is significant for structural condition assessment in
structural health monitoring (SHM). Current advanced methods usually employ deep …
structural health monitoring (SHM). Current advanced methods usually employ deep …
Structural dynamic response reconstruction using self-attention enhanced generative adversarial networks
In structural health monitoring (SHM) of civil engineering structures, loss of measured
structural responses inevitably occurs in practice, especially when structures encounter …
structural responses inevitably occurs in practice, especially when structures encounter …
[HTML][HTML] Deep learning-based structural health monitoring
This article provides a comprehensive review of deep learning-based structural health
monitoring (DL-based SHM). It encompasses a broad spectrum of DL theories and …
monitoring (DL-based SHM). It encompasses a broad spectrum of DL theories and …