Structural Health Monitoring-An International Journal

Papers
(The H4-Index of Structural Health Monitoring-An International Journal is 34. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-09-01 to 2025-09-01.)
ArticleCitations
A novel fault evaluation method based on nonlinear vibration features and Euclidean distance measurement for grid-like structures230
Structural nonlinear damage identification based on the information distance of GNPAX/GARCH model and its experimental study151
Interpretable convolutional sparse coding method of Lamb waves for damage identification and localization131
Modeling of an aircraft structural health monitoring sensor network for operational impact assessment76
Hybrid artificial intelligence-based inference models for accurately predicting dam body displacements: A case study of the Fei Tsui dam74
Multimodal feature fusion for detecting debonding in FRP-reinforced concrete interfaces using dual-branch CNN60
Model uncertainty quantification of a degradation model of miter gates using normalizing flow-based likelihood-free inference56
20 years of monitoring of a steel jacket offshore platform: variability of environmental and modal parameters55
A novel edge intelligence application model with lightweight network and antinoise ability for bearing fault diagnosis55
Multi-modal model updating of miter gates on navigational locks55
Vibration-based monitoring of a super tall building with TMD during typhoon Ampil52
Imaging cracks in orthotropic steel decks based on guided wave and variational Bayesian robust principal component analysis52
Meta-model structural monitoring with cutting-edge AAE-VMD fusion alongside optimized machine learning methods50
Entire loosening stage monitoring of bolted joints via nonlinear electro-mechanical impedance spectroscopy49
U2CrackNet: a deeper architecture with two-level nested U-structure for pavement crack detection46
Small-sample damage detection of bleacher structure based on GAN and MSS-CNN models46
Analysis of the galleries cracking causes in the backfill area of pumped storage power station based on monitoring and numerical simulation: a case study of Hohhot upper reservoir46
Multi-level damage diagnosis on stiffened composite panels based on a damage-uninformative digital twin45
Wind turbine gearbox fault diagnosis via adaptive IMFogram44
Potential and limitations of NARX for defect detection in guided wave signals44
Bayesian system identification considering the spatial correlation of distributed loads43
An intelligent detection approach for multi-part cover based on deep learning under unbalanced and small size samples43
Extracting and identifying essential characteristics of gear pitting and cracks with consideration of fault mechanisms40
Multivariate variational mode decomposition and generalized composite multiscale permutation entropy for multichannel fault diagnosis of hoisting machinery system39
Enhancing Lamb wave-based damage diagnosis in composite materials using a pseudo-damage boosted convolutional neural network approach38
Heterogeneous structural responses recovery based on multi-modal deep learning37
Percussion-based loosening detection method for multi-bolt structure using convolutional neural network DenseNet-CBAM37
Dynamical modeling of spur gear with pitting based on image processing tooth surface37
Bridge inspection component registration for damage evolution37
Laboratory and field experiment validations on the use of hydraulic transients for estimating buried water pipeline deterioration37
Physics-informed deep learning for scattered full wavefield reconstruction from a sparse set of sensor data for impact diagnosis in structural health monitoring35
Multiple-input, multiple-output modal testing of a Hawk T1A aircraft: a new full-scale dataset for structural health monitoring35
Vibration-based structural damage localization through a discriminant analysis strategy with cepstral coefficients34
Looseness monitoring of multiple M1 bolt joints using multivariate intrinsic multiscale entropy analysis and Lorentz signal-enhanced piezoelectric active sensing34
Bridge damage detection using unsupervised learning with vehicle-induced vibrations34
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