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Structural Health Monitoring

Papers

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Showing 1–50 of 197 papers

TitleStatusHype
Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systemsCode1
Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural NetworksCode1
Neural Extended Kalman Filters for Learning and Predicting Dynamics of Structural SystemsCode1
NeuralSI: Structural Parameter Identification in Nonlinear Dynamical SystemsCode1
Dataset: Impact Events for Structural Health Monitoring of a Plastic Thin PlateCode1
Active management of battery degradation in wireless sensor network using deep reinforcement learning for group battery replacement—0
A CMOS SoC for Wireless Ultrasonic Power/Data Transfer and SHM Measurements on Structures—0
1D Convolutional Neural Networks and Applications: A Survey—0
A generalised form for a homogeneous population of structures using an overlapping mixture of Gaussian processes—0
A Fast Parallel Tensor Decomposition with Optimal Stochastic Gradient Descent: an Application in Structural Damage Identification—0
A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methods—0
Active learning for regression in engineering populations: A risk-informed approach—0
A Machine Learning-Driven Wireless System for Structural Health Monitoring—0
A Meta-Learning Approach to Population-Based Modelling of Structures—0
A Convolutional Cost-Sensitive Crack Localization Algorithm for Automated and Reliable RC Bridge Inspection—0
A Computational Framework for Modeling Complex Sensor Network Data Using Graph Signal Processing and Graph Neural Networks in Structural Health Monitoring—0
A decision framework for selecting information-transfer strategies in population-based SHM—0
A Bayesian methodology for localising acoustic emission sources in complex structures—0
Applied Bayesian Structural Health Monitoring: inclinometer data anomaly detection and forecasting—0
A Programmable CMOS Transceiver for Structural Health Monitoring—0
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic—0
A robust deep learning-based damage identification approach for SHM considering missing data—0
A Tensor-based Structural Health Monitoring Approach for Aeroservoelastic Systems—0
A topological analysis of cointegrated data: a Z24 Bridge case study—0
Automated Detection and Analysis of Minor Deformations in Flat Walls Due to Railway Vibrations Using LiDAR and Machine Learning—0
A Hierarchical Deep Convolutional Neural Network and Gated Recurrent Unit Framework for Structural Damage Detection—0
Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions—0
Balanced Semi-Supervised Generative Adversarial Network for Damage Assessment from Low-Data Imbalanced-Class Regime—0
Incremental Bayesian tensor learning for structural monitoring data imputation and response forecasting—0
B-BACN: Bayesian Boundary-Aware Convolutional Network for Crack Characterization—0
BOTDA Fiber Sensor System Based on FPGA Accelerated Support Vector Regression—0
A Nonparametric Unsupervised Learning Approach for Structural Damage Detection—0
Blind Identification of State-Space Models in Physical Coordinates—0
Better Together: Using Multi-task Learning to Improve Feature Selection within Structural Datasets—0
Bridging the Reality Gap in Digital Twins with Context-Aware, Physics-Guided Deep Learning—0
An optimal baseline selection methodology for data-driven damage detection and temperature compensation in acousto-ultrasonics—0
A physics-informed machine learning model for reconstruction of dynamic loads—0
CNN-Based Structural Damage Detection using Time-Series Sensor Data—0
Comparison of Tiny Machine Learning Techniques for Embedded Acoustic Emission Analysis—0
Compressive-Sensing Data Reconstruction for Structural Health Monitoring: A Machine-Learning Approach—0
Concrete Surface Crack Detection with Convolutional-based Deep Learning Models—0
Conditional deep generative models as surrogates for spatial field solution reconstruction with quantified uncertainty in Structural Health Monitoring applications—0
CrackESS: A Self-Prompting Crack Segmentation System for Edge Devices—0
Crack Semantic Segmentation using the U-Net with Full Attention Strategy—0
CycleGAN for Undamaged-to-Damaged Domain Translation for Structural Health Monitoring and Damage Detection—0
Damage detection in an uncertain nonlinear beam based on stochastic Volterra series—0
Damage detection in operational wind turbine blades using a new approach based on machine learning—0
Damage detection using in-domain and cross-domain transfer learning—0
Damage identification for bridges using machine learning: Development and application to KW51 bridge—0
Anomaly Detection in Offshore Wind Turbine Structures using Hierarchical Bayesian Modelling—0
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