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Structural Health Monitoring

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Showing 101–150 of 197 papers

TitleStatusHype
Structural State Translation: Condition Transfer between Civil Structures Using Domain-Generalization for Structural Health Monitoring—0
Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systemsCode1
Zero-Shot Transfer Learning for Structural Health Monitoring using Generative Adversarial Networks and Spectral MappingCode0
Balanced Semi-Supervised Generative Adversarial Network for Damage Assessment from Low-Data Imbalanced-Class Regime—0
Deep learning for structural health monitoring: An application to heritage structures—0
Improving aircraft performance using machine learning: a review—0
Self-learning locally-optimal hypertuning using maximum entropy, and comparison of machine learning approaches for estimating fatigue life in composite materials—0
Semi-supervised detection of structural damage using Variational Autoencoder and a One-Class Support Vector Machine—0
Neural Extended Kalman Filters for Learning and Predicting Dynamics of Structural SystemsCode1
Physically Meaningful Uncertainty Quantification in Probabilistic Wind Turbine Power Curve Models as a Damage Sensitive Feature—0
Dataset: Impact Events for Structural Health Monitoring of a Plastic Thin PlateCode1
A topological analysis of cointegrated data: a Z24 Bridge case study—0
On topological data analysis for structural dynamics: an introduction to persistent homology—0
On topological data analysis for SHM; an introduction to persistent homology—0
NeuralSI: Structural Parameter Identification in Nonlinear Dynamical SystemsCode1
On an Application of Generative Adversarial Networks on Remaining Lifetime Estimation—0
Physics-informed machine learning for Structural Health Monitoring—0
A generalised form for a homogeneous population of structures using an overlapping mixture of Gaussian processes—0
Improving decision-making via risk-based active learning: Probabilistic discriminative classifiers—0
On statistic alignment for domain adaptation in structural health monitoringCode0
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations—0
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic—0
Lost Vibration Test Data Recovery Using Convolutional Neural Network: A Case Study—0
Modelling variability in vibration-based PBSHM via a generalised population form—0
Exploring Scalable, Distributed Real-Time Anomaly Detection for Bridge Health MonitoringCode0
On partitioning of an SHM problem and parallels with transfer learning—0
On an application of graph neural networks in population based SHM—0
On generating parametrised structural data using conditional generative adversarial networks—0
CycleGAN for Undamaged-to-Damaged Domain Translation for Structural Health Monitoring and Damage Detection—0
What's Cracking? A Review and Analysis of Deep Learning Methods for Structural Crack Segmentation, Detection and Quantification—0
Time-varying Identification of Guided Wave Propagation under Varying Temperature via Non-Stationary Time Series Models—0
On robust risk-based active-learning algorithms for enhanced decision support—0
Generative Adversarial Networks for Labelled Vibration Data Generation—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
Environmental variation compensated damage classification and localization in ultrasonic guided wave SHM using self-learnt features and Gaussian mixture models—0
A Fast Parallel Tensor Decomposition with Optimal Stochastic Gradient Descent: an Application in Structural Damage Identification—0
A CMOS SoC for Wireless Ultrasonic Power/Data Transfer and SHM Measurements on Structures—0
Blind Identification of State-Space Models in Physical Coordinates—0
Wave-Informed Matrix Factorization with Global Optimality Guarantees—0
Gaussian Process Regression for Active Sensing Probabilistic Structural Health Monitoring: Experimental Assessment Across Multiple Damage and Loading Scenarios—0
Canonical-Correlation-Based Fast Feature Selection for Structural Health MonitoringCode0
On risk-based active learning for structural health monitoring—0
A Computational Framework for Modeling Complex Sensor Network Data Using Graph Signal Processing and Graph Neural Networks in Structural Health Monitoring—0
Crack Semantic Segmentation using the U-Net with Full Attention Strategy—0
Prediction of Ultrasonic Guided Wave Propagation in Solid-fluid and their Interface under Uncertainty using Machine Learning—0
Wave based damage detection in solid structures using artificial neural networks—0
Online structural health monitoring by model order reduction and deep learning algorithms—0
Data-driven method for real-time prediction and uncertainty quantification of fatigue failure under stochastic loading using artificial neural networks and Gaussian process regression—0
Foundations of Population-Based SHM, Part IV: The Geometry of Spaces of Structures and their Feature Spaces—0
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