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Structural Health Monitoring

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Showing 1–50 of 197 papers

TitleStatusHype
Digital twin for virtual sensing of ferry quays via a Gaussian Process Latent Force Model—0
Structural Vibration Monitoring with Diffractive Optical Processors—0
Mechanical in-sensor computing: a programmable meta-sensor for structural damage classification without external electronic power—0
Bridging the Reality Gap in Digital Twins with Context-Aware, Physics-Guided Deep Learning—0
Localization of Impacts on Thin-Walled Structures by Recurrent Neural Networks: End-to-end Learning from Real-World Data—0
On-Device Crack Segmentation for Edge Structural Health Monitoring—0
Fault Diagnosis of 3D-Printed Scaled Wind Turbine Blades—0
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models—0
Towards a Universal Vibration Analysis Dataset: A Framework for Transfer Learning in Predictive Maintenance and Structural Health Monitoring—0
Guided Wave-Based Structural Awareness Under Varying Operating States via Manifold Representations—0
A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methods—0
An optimal baseline selection methodology for data-driven damage detection and temperature compensation in acousto-ultrasonics—0
Active management of battery degradation in wireless sensor network using deep reinforcement learning for group battery replacement—0
Efficient dynamic modal load reconstruction using physics-informed Gaussian processes based on frequency-sparse Fourier basis functionsCode0
Real-Time Structural Deflection Estimation in Hydraulically Actuated Systems Using 3D Flexible Multibody Simulation and DNNs—0
Survey of Quantization Techniques for On-Device Vision-based Crack Detection—0
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM—0
Vision-based autonomous structural damage detection using data-driven methods—0
Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions—0
Data-driven Detection and Evaluation of Damages in Concrete Structures: Using Deep Learning and Computer Vision—0
On the use of Statistical Learning Theory for model selection in Structural Health Monitoring—0
Automated Detection and Analysis of Minor Deformations in Flat Walls Due to Railway Vibrations Using LiDAR and Machine Learning—0
CrackESS: A Self-Prompting Crack Segmentation System for Edge Devices—0
MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery—0
Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data—0
Signal-based online acceleration and strain data fusion using B-splines and Kalman filter for full-field dynamic displacement estimation—0
When does a bridge become an aeroplane?—0
NonSysId: A nonlinear system identification package with improved model term selection for NARMAX models—0
Comparison of Tiny Machine Learning Techniques for Embedded Acoustic Emission Analysis—0
Deep Learning for Micro-Scale Crack Detection on Imbalanced Datasets Using Key Point Localization—0
Multi-temporal crack segmentation in concrete structure using deep learning approaches—0
Deep Learning-Based Fatigue Cracks Detection in Bridge Girders using Feature Pyramid Networks—0
Addressing the Pitfalls of Image-Based Structural Health Monitoring: A Focus on False Positives, False Negatives, and Base Rate Bias—0
Multi-input Multi-output Loewner Framework for Vibration-based Damage Detection on a Trainer Jet—0
Very High-Resolution Bridge Deformation Monitoring Using UAV-based Photogrammetry—0
Deep learning-based Visual Measurement Extraction within an Adaptive Digital Twin Framework from Limited Data Using Transfer Learning—0
Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural NetworksCode1
Data-driven Framework for Forward and Inverse Problems in Guided Waves-Based Structural Health Monitoring Under Varying Environmental and Operating Conditions—0
On the topology and geometry of population-based SHM—0
Towards an active-learning approach to resource allocation for population-based damage prognosis—0
A Machine Learning-Driven Wireless System for Structural Health Monitoring—0
Damage detection in an uncertain nonlinear beam based on stochastic Volterra series—0
Active learning for regression in engineering populations: A risk-informed approach—0
Multitask learning for improved scour detection: A dynamic wave tank studyCode0
Damage identification for bridges using machine learning: Development and application to KW51 bridge—0
Structural damage detection via hierarchical damage information with volumetric assessment—0
Quantifying the value of positive transfer: An experimental case study—0
Deep learning architectures for data-driven damage detection in nonlinear dynamic systems—0
Enhancing robustness of data-driven SHM models: adversarial training with circle loss—0
Multiple-input, multiple-output modal testing of a Hawk T1A aircraft: A new full-scale dataset for structural health monitoring—0
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