专题：Structural Health Monitoring Techniques

This cluster of papers covers advancements in structural health monitoring techniques, including vibration-based damage identification, wireless sensor networks, modal identification, structural damage detection, model updating, Bayesian system identification, deep learning applications, sensor networks, environmental effects, and nonlinear dynamics.
最新文献
Meta-Learning-Based Graph Convolutional Wavelet Network for Intelligent Dynamic Modeling of High-Speed Rail Subsystems

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Structural Performance Warning Based on Computer Intelligent Monitoring and Fractional-Order Multi-Rate Kalman Fusion Method

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A comprehensive review of indirect bridge health monitoring

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A novel hybrid algorithm for damage detection in bridge foundations under complex underwater environments using ROV capture pictures

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A machine learning and multi-source authentic data-driven framework for accurate fatigue life prediction of welds in existing steel bridge decks

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UAV-based quantitative crack measurement for bridges integrating four-point laser metric calibration and mamba segmentation

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Interval theory-embedded data-driven identification framework for uncertain thermo-elastic parameters

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Bayesian optimization CNN-LSTM neural network for fatigue life prediction of Rib-to-deck Welds in orthotropic steel decks

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A label-free physics informed neural network with hard constraints and Fourier features spectrally-enhanced for multi-frequency seismic structural dynamic response

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Uncertainty-aware, high-precision multi-step prediction of structural health monitoring sensor streams under extreme typhoon events: an enhanced Bayesian dynamic linear model leveraging the kernel regression basis function for severe environmental adaptation

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近5年高被引文献
Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis

article Full Text OpenAlex 893 FWCI96.4281

Machine learning for structural engineering: A state-of-the-art review

article Full Text OpenAlex 748 FWCI64.3789

A Systematic Review of Advanced Sensor Technologies for Non-Destructive Testing and Structural Health Monitoring

review Full Text OpenAlex 492 FWCI10.1705

Structural health monitoring of civil engineering structures by using the internet of things: A review

article Full Text OpenAlex 484 FWCI46.727

Deep learning-based structural health monitoring

article Full Text OpenAlex 433 FWCI72.5558

Deep learning to estimate lithium-ion battery state of health without additional degradation experiments

article Full Text OpenAlex 415 FWCI30.1723

Vibration feature extraction using signal processing techniques for structural health monitoring: A review

article Full Text OpenAlex 401 FWCI35.1289

A Novel State-of-Health Estimation for the Lithium-Ion Battery Using a Convolutional Neural Network and Transformer Model

article Full Text OpenAlex 382 FWCI18.8733

Integrated structural health monitoring in bridge engineering

article Full Text OpenAlex 380 FWCI30.8974

An improved CNN-LSTM model-based state-of-health estimation approach for lithium-ion batteries

article Full Text OpenAlex 371 FWCI26.7112