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Advanced data reconstruction for vibration-based damage detection using a Cauchy–Schwarz Variational Autoencoder utilising a Spatial-Auto-Temporal Thermal Consistency Model

https://doi.org/10.2139/ssrn.5669011
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Time series data recovery in SHM of large-scale bridges: Leveraging GAN and Bi-LSTM networks
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3D torsional experimental strain modal analysis for structural health monitoring using piezoelectric sensors
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Missing measurement data recovery methods in structural health monitoring: The state, challenges and case study
inferredcites →https://doi.org/10.1016/j.ymssp.2010.12.017openalex-snapshot
Dynamic testing of a damaged bridge
inferredcites →https://doi.org/10.1063/1.3591837openalex-snapshot
I35W COLLAPSE, REBUILD, AND STRUCTURAL HEALTH MONITORING—CHALLENGES ASSOCIATED WITH STRUCTURAL HEALTH MONITORING OF BRIDGE SYSTEMS
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Unsupervised Anomaly Video Detection via a Double-Flow ConvLSTM Variational Autoencoder
inferredcites →https://doi.org/10.1109/tmm.2023.3268870openalex-snapshot
CS-IntroVAE: Cauchy-Schwarz Divergence-Based Introspective Variational Autoencoder
inferredcites →https://doi.org/10.1111/mice.12850openalex-snapshot
Lost data neural semantic recovery framework for structural health monitoring based on deep learning
inferredcites →https://doi.org/10.1142/s0219455419500925openalex-snapshot
A Generative Adversarial Network Model for Simulating Various Types of Human-Induced Loads
inferredcites →https://doi.org/10.1177/1475921718794953openalex-snapshot
Bayesian multi-task learning methodology for reconstruction of structural health monitoring data
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Dynamic response reconstruction for structural health monitoring using densely connected convolutional networks
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Group sparsity-aware convolutional neural network for continuous missing data recovery of structural health monitoring
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A hybrid method coupling empirical mode decomposition and a long short-term memory network to predict missing measured signal data of SHM systems
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Lost data reconstruction for structural health monitoring using deep convolutional generative adversarial networks
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Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring
inferredcites →https://doi.org/10.1186/s40069-022-00557-1openalex-snapshot
An Overview: The Application of Vibration-Based Techniques in Bridge Structural Health Monitoring
inferredcites →https://doi.org/10.1520/jte20130166openalex-snapshot
Forced-Vibration Testing and Experimental Modal Analysis of a Steel Footbridge for Structural Identification
inferredcites →https://doi.org/10.3846/13923730.2011.632489openalex-snapshot
MODAL ANALYSIS OF BRIDGE STRUCTURES BY MEANS OF FORCED VIBRATION TESTS / TILTO KONSTRUKCIJŲ MODALINĖ ANALIZĖ TAIKANT PRIVERSTINĖS VIBRACIJOS TESTUS
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