Abstract
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Haiyang Li, Ruijie Xi, Yilin Xie, Xiaolin Meng, Shuguang Wu
Abstract
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An IoT-based road bridge health monitoring and warning system
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Data normalization for the continuous monitoring of a steel truss bridge: A case study from the Italian railway line
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Probabilistic method for wind speed prediction and statistics distribution inference based on SHM data-driven
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Short-term damage alarming with limited vibration data in bridge structures: a fully non-parametric machine learning technique
Provenance
crossref
Confidence 100%
openalex
Confidence 95%
datacite
Confidence 0%
10.1016/j.measurement.2024.114935 · 2024
On continuous health monitoring of bridges under serious environmental variability by an innovative multi-task unsupervised learning method
10.1080/15732479.2023.2166538 · 2024
Non-parametric empirical machine learning for short-term and long-term structural health monitoring
10.1177/14759217211069842 · 2022
The impact of sensing parameters on data management and anomaly detection in structural health monitoring
10.1007/s13349-022-00566-4 · 2022
Three decades of statistical pattern recognition paradigm for SHM of bridges
10.1177/14759217221075241 · 2022
Asset management, condition monitoring and Digital Twins: damage detection and virtual inspection on a reinforced concrete bridge
10.1080/15732479.2024.2311911 · 2024
Integrated structural health monitoring in bridge engineering
10.1016/j.autcon.2022.104168 · 2022
Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring
10.1177/14759217211021942 · 2022
Reducing false alarms in structural health monitoring systems by exploiting time information via binomial distribution classifier
10.1016/j.ymssp.2023.110938 · 2024
Decision-making styles, integrity and perceived stress in police offices
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Physics-guided diagnosis framework for bridge health monitoring using raw vehicle accelerations
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Lite detr: an interleaved multi-scale encoder for efficient detr
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Transforming structural health monitoring: leveraging multi-source data fusion with two stage encoder transformer for bridge deformation prediction
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Unsupervised machine anomaly detection using autoencoder and temporal convolutional network
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Wavelet-based denoising of structural health monitoring strain measurements
10.1016/j.measen.2025.101974 · 2025
Proposed machine learning techniques for bridge structural health monitoring: a laboratory study
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Transfer learning-based data anomaly detection for structural health monitoring
10.1177/14759217221142174 · 2023
Development and experimental verification of an IoT sensing system for drive-by bridge health monitoring
10.1016/j.engstruct.2023.116705 · 2023
Real-time outlier detection in integrated GNSS and accelerometer structural health monitoring systems based on a robust multi-rate kalman filter
10.1007/s00190-023-01724-2 · 2023
Probabilistic autoencoder-based bridge damage assessment using train-induced responses
10.1016/j.ymssp.2023.111046 · 2024
Contact point response-based indirect bridge health monitoring using robust empirical mode decomposition
10.1016/j.jsv.2023.118064 · 2023
A review of bridge health monitoring based on machine learning
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Predicting bridge longitudinal displacement from monitored operational loads with hierarchical CNN for condition assessment
10.1016/j.ymssp.2023.110623 · 2023
Damage detection in bridge structures through compressed sensing of crowdsourced smartphone data
10.1155/2024/5436675 · 2024
Dynamic threshold cable-stayed bridge health monitoring system based on temperature effect correction
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Structural health monitoring of railway bridges using innovative sensing technologies and machine learning algorithms: a concise review
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A review of methods and applications in structural health monitoring (SHM) for bridges
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Robust sliding window CFAR detection based on quantile truncated statistics
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A review of methods and applications in structural health monitoring (SHM) for bridges
10.1016/j.measurement.2024.116575 · doi-reference
Dynamic threshold cable-stayed bridge health monitoring system based on temperature effect correction
10.3390/s23218826 · doi-reference
Damage detection in bridge structures through compressed sensing of crowdsourced smartphone data
10.1155/2024/5436675 · doi-reference
Predicting bridge longitudinal displacement from monitored operational loads with hierarchical CNN for condition assessment
10.1016/j.ymssp.2023.110623 · doi-reference
Contact point response-based indirect bridge health monitoring using robust empirical mode decomposition
10.1016/j.jsv.2023.118064 · doi-reference
Probabilistic autoencoder-based bridge damage assessment using train-induced responses
10.1016/j.ymssp.2023.111046 · doi-reference
Real-time outlier detection in integrated GNSS and accelerometer structural health monitoring systems based on a robust multi-rate kalman filter
10.1007/s00190-023-01724-2 · doi-reference
Development and experimental verification of an IoT sensing system for drive-by bridge health monitoring
10.1016/j.engstruct.2023.116705 · doi-reference
Transfer learning-based data anomaly detection for structural health monitoring
10.1177/14759217221142174 · doi-reference
Proposed machine learning techniques for bridge structural health monitoring: a laboratory study
10.3390/rs15081984 · doi-reference
Wavelet-based denoising of structural health monitoring strain measurements
10.1016/j.measen.2025.101974 · doi-reference
Physics-guided diagnosis framework for bridge health monitoring using raw vehicle accelerations
10.1016/j.ymssp.2023.110899 · doi-reference
Reducing false alarms in structural health monitoring systems by exploiting time information via binomial distribution classifier
10.1016/j.ymssp.2023.110938 · doi-reference
Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring
10.1177/14759217211021942 · doi-reference
Integrated structural health monitoring in bridge engineering
10.1016/j.autcon.2022.104168 · doi-reference
Asset management, condition monitoring and Digital Twins: damage detection and virtual inspection on a reinforced concrete bridge
10.1080/15732479.2024.2311911 · doi-reference
Three decades of statistical pattern recognition paradigm for SHM of bridges
10.1177/14759217221075241 · doi-reference
The impact of sensing parameters on data management and anomaly detection in structural health monitoring
10.1007/s13349-022-00566-4 · doi-reference
Non-parametric empirical machine learning for short-term and long-term structural health monitoring
10.1177/14759217211069842 · doi-reference
On continuous health monitoring of bridges under serious environmental variability by an innovative multi-task unsupervised learning method
10.1080/15732479.2023.2166538 · doi-reference
Short-term damage alarming with limited vibration data in bridge structures: a fully non-parametric machine learning technique
10.1016/j.measurement.2024.114935 · doi-reference
Probabilistic method for wind speed prediction and statistics distribution inference based on SHM data-driven
10.1016/j.probengmech.2023.103475 · doi-reference
Decoupled kullback-leibler divergence loss
10.52202/079017-2370 · doi-reference
A feature extraction & selection benchmark for structural health monitoring
10.1177/14759217221111141 · doi-reference
Segnet: a deep convolutional encoder-decoder architecture for image segmentation
10.1109/tpami.2016.2644615 · doi-reference
Data normalization for the continuous monitoring of a steel truss bridge: A case study from the Italian railway line
10.1016/j.iintel.2025.100171 · doi-reference
Decision-Aid framework for face authentication detection using ResNext50 and BiLSTM to enhance media integrity
10.1109/access.2025.3569792 · doi-reference
An IoT-based road bridge health monitoring and warning system
10.3390/s24020469 · doi-reference