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Structural Health Monitoring

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Showing 51–100 of 197 papers

TitleStatusHype
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models—0
Deep learning architectures for data-driven damage detection in nonlinear dynamic systems—0
Deep Learning-Based Fatigue Cracks Detection in Bridge Girders using Feature Pyramid Networks—0
Deep learning-based Visual Measurement Extraction within an Adaptive Digital Twin Framework from Limited Data Using Transfer Learning—0
Deep Learning for Micro-Scale Crack Detection on Imbalanced Datasets Using Key Point Localization—0
Deep learning for structural health monitoring: An application to heritage structures—0
Deep Learning Overloaded Vehicle Identification for Long Span Bridges Based on Structural Health Monitoring Data—0
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations—0
Deterministic and statistical calibration of constitutive models from full-field data with parametric physics-informed neural networks—0
Digital twin for virtual sensing of ferry quays via a Gaussian Process Latent Force Model—0
Distributed Machine Learning in Materials that Couple Sensing, Actuation, Computation and Communication—0
Effect of noise on output-only modal identification of beams—0
Enhancing In-Situ Structural Health Monitoring through RF Energy-Powered Sensor Nodes and Mobile Platform—0
Enhancing robustness of data-driven SHM models: adversarial training with circle loss—0
Environmental variation compensated damage classification and localization in ultrasonic guided wave SHM using self-learnt features and Gaussian mixture models—0
Fault Diagnosis of 3D-Printed Scaled Wind Turbine Blades—0
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM—0
Foundations of Population-Based SHM, Part IV: The Geometry of Spaces of Structures and their Feature Spaces—0
From Classification to Segmentation with Explainable AI: A Study on Crack Detection and Growth Monitoring—0
Full-scale modal testing of a Hawk T1A aircraft for benchmarking vibration-based methods—0
Fully convolutional networks for structural health monitoring through multivariate time series classification—0
Fully Data-Driven Model for Increasing Sampling Rate Frequency of Seismic Data using Super-Resolution Generative Adversarial Networks—0
Gaussian Process Regression for Active Sensing Probabilistic Structural Health Monitoring: Experimental Assessment Across Multiple Damage and Loading Scenarios—0
Generative Adversarial Networks for Data Generation in Structural Health Monitoring—0
Generative Adversarial Networks for Labeled Acceleration Data Augmentation for Structural Damage Detection—0
Generative Adversarial Networks for Labelled Vibration Data Generation—0
Guided Wave-Based Structural Awareness Under Varying Operating States via Manifold Representations—0
Hierarchical sparse Bayesian learning: theory and application for inferring structural damage from incomplete modal data—0
Improved Support Recovery Guarantees for the Group Lasso With Applications to Structural Health Monitoring—0
Improving aircraft performance using machine learning: a review—0
Improving decision-making via risk-based active learning: Probabilistic discriminative classifiers—0
Integrating Edge-AI in Structural Health Monitoring domain—0
Intensity-Based Feature Selection for Near Real-Time Damage Diagnosis of Building Structures—0
Leveraging Gaussian Process and Voting-Empowered Many-Objective Evaluation for Fault Identification—0
Leveraging SPD Matrices on Riemannian Manifolds in Quantum Classical Hybrid Models for Structural Health Monitoring—0
Localization of Impacts on Thin-Walled Structures by Recurrent Neural Networks: End-to-end Learning from Real-World Data—0
Lost Vibration Test Data Recovery Using Convolutional Neural Network: A Case Study—0
Machine-learning-based methods for output only structural modal identification—0
Manifold learning-based feature extraction for structural defect reconstruction—0
Mechanical in-sensor computing: a programmable meta-sensor for structural damage classification without external electronic power—0
Mechanics-Informed Autoencoder Enables Automated Detection and Localization of Unforeseen Structural Damage—0
Modelling variability in vibration-based PBSHM via a generalised population form—0
Model Uncertainty Quantification for Reliable Deep Vision Structural Health Monitoring—0
MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery—0
Multi-input Multi-output Loewner Framework for Vibration-based Damage Detection on a Trainer Jet—0
Multi-Objective Variational Autoencoder: an Application for Smart Infrastructure Maintenance—0
Multiple-input, multiple-output modal testing of a Hawk T1A aircraft: A new full-scale dataset for structural health monitoring—0
Multi-temporal crack segmentation in concrete structure using deep learning approaches—0
NeCPD: An Online Tensor Decomposition with Optimal Stochastic Gradient Descent—0
Neural operator for structural simulation and bridge health monitoring—0
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