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Structural Health Monitoring

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Showing 76–100 of 197 papers

TitleStatusHype
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
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