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A review of computer vision–based structural health monitoring at local and global levels

Structural Health Monitoring, 2020
Structural health monitoring at local and global levels using computer vision technologies has gained much attention in the structural health monitoring community in research and practice. Due to the computer vision technology application advantages such
C. Dong, N. Catbas
semanticscholar   +1 more source

A Feature Extraction & Selection Benchmark for Structural Health Monitoring

Structural Health Monitoring, 2022
There are a large number of time domain, frequency domain and time-frequency signal processing methods available for univariate feature extraction.
T. Buckley, Bidisha Ghosh, V. Pakrashi
semanticscholar   +1 more source

Monitoring the curing process of in-situ concrete with piezoelectric-based techniques – A practical application

Structural Health Monitoring, 2022
The stiffness and strength properties of freshly poured concrete develop over time as the concrete hardens due to curing. The monitoring of such properties therefore enables timely construction decisions such as formwork removal.
Z. Tang   +5 more
semanticscholar   +1 more source

Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring

Structural Health Monitoring, 2021
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 type.
Huachen Jiang   +4 more
semanticscholar   +1 more source

Machine learning paradigm for structural health monitoring

Structural Health Monitoring, 2020
Structural health diagnosis and prognosis is the goal of structural health monitoring. Vibration-based structural health monitoring methodology has been extensively investigated.
Y. Bao, Hui Li
semanticscholar   +1 more source

Toward data anomaly detection for automated structural health monitoring: Exploiting generative adversarial nets and autoencoders

Structural Health Monitoring, 2020
Damage detection is one of the most important tasks for structural health monitoring of civil infrastructure. Before a damage detection algorithm can be applied, the integrity of the data must be ensured; otherwise results may be misleading or incorrect.
J. Mao, Hongya Wang, B. Spencer
semanticscholar   +1 more source

A review of structural health monitoring of bonded structures using electromechanical impedance spectroscopy

Structural Health Monitoring, 2021
The article presents a literature review of electromechanical impedance spectroscopy for structural health monitoring, with emphasis in adhesively bonded joints.
A. Tenreiro   +2 more
semanticscholar   +1 more source

Lost data reconstruction for structural health monitoring using deep convolutional generative adversarial networks

Structural Health Monitoring, 2020
In the application of structural health monitoring, the measured data might be temporarily or permanently lost due to sensor fault or transmission failure.
Xiao-Jun Lei, Limin Sun, Ye Xia
semanticscholar   +1 more source

Recent progress in aircraft smart skin for structural health monitoring

Structural Health Monitoring, 2021
Through the integration of advanced sensors, actuators, and micro-processors, aircraft smart skin technology can improve the structural performance of aircraft and make them self-perception, self-diagnosis, self-adaptation, self-learning, and self-repair.
Yu Wang   +4 more
semanticscholar   +1 more source

Therapeutic Drug Monitoring of Antibiotics: Defining the Therapeutic Range

Therapeutic Drug Monitoring, 2021
Purpose: In the present narrative review, the authors aimed to discuss the relationship between the pharmacokinetic/pharmacodynamic (PK/PD) of antibiotics and clinical response (including efficacy and toxicity).
M. Abdul-Aziz   +3 more
semanticscholar   +1 more source

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