OOIR: Observatory of International Research

Papers

(The H4-Index of Mechanical Systems and Signal Processing is 79. 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 2020-04-01 to 2024-04-01.)

Article	Citations
Applications of machine learning to machine fault diagnosis: A review and roadmap	1338
1D convolutional neural networks and applications: A survey	1018
A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications	580
Model predictive control of three-axis gimbal system mounted on UAV for real-time target tracking under external disturbances	340
A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges	316
A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks	284
Signal based condition monitoring techniques for fault detection and diagnosis of induction motors: A state-of-the-art review	268
Damage detection techniques for wind turbine blades: A review	197
A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings	185
Recent progress of chatter prediction, detection and suppression in milling	182
A new data-driven transferable remaining useful life prediction approach for bearing under different working conditions	174
Multisensor data fusion for gearbox fault diagnosis using 2-D convolutional neural network and motor current signature analysis	172
A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning	167
A spatial coupling model to study dynamic performance of pantograph-catenary with vehicle-track excitation	148
A novel anomaly detection method based on adaptive Mahalanobis-squared distance and one-class kNN rule for structural health monitoring under environmental effects	144
A review on control strategies for compensation of hysteresis and creep on piezoelectric actuators based micro systems	142
A new deep auto-encoder method with fusing discriminant information for bearing fault diagnosis	141
Digital twin, physics-based model, and machine learning applied to damage detection in structures	139
Fault feature extraction of rotating machinery using a reweighted complete ensemble empirical mode decomposition with adaptive noise and demodulation analysis	139
Multistability phenomenon in signal processing, energy harvesting, composite structures, and metamaterials: A review	138
An improved genetic algorithm optimization fuzzy controller applied to the wellhead back pressure control system	138
Residual joint adaptation adversarial network for intelligent transfer fault diagnosis	134
Meshing and dynamic characteristics analysis of spalled gear systems: A theoretical and experimental study	134
An enhanced selective ensemble deep learning method for rolling bearing fault diagnosis with beetle antennae search algorithm	134
Deep digital twins for detection, diagnostics and prognostics	133

A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis	132
Metamaterial beam with graded local resonators for broadband vibration suppression	128
Bearing fault diagnosis method based on adaptive maximum cyclostationarity blind deconvolution	127
A hybrid classification autoencoder for semi-supervised fault diagnosis in rotating machinery	126
A novel time–frequency Transformer based on self–attention mechanism and its application in fault diagnosis of rolling bearings	126
Vibration control based metamaterials and origami structures: A state-of-the-art review	125
A review of vibration-based gear wear monitoring and prediction techniques	124
Application of neural network algorithm in fault diagnosis of mechanical intelligence	124
The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study	123
The sum of weighted normalized square envelope: A unified framework for kurtosis, negative entropy, Gini index and smoothness index for machine health monitoring	122
Bearing fault diagnosis via generalized logarithm sparse regularization	121
An explainable artificial intelligence approach for unsupervised fault detection and diagnosis in rotating machinery	116
CNN-LSTM deep learning architecture for computer vision-based modal frequency detection	113
Hybrid composite meta-porous structure for improving and broadening sound absorption	113
A hybrid piezo-dielectric wind energy harvester for high-performance vortex-induced vibration energy harvesting	113
A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests	111
Digital twin-driven intelligent assessment of gear surface degradation	111
Recursive sliding mode control with adaptive disturbance observer for a linear motor positioner	110
Knowledge mapping-based adversarial domain adaptation: A novel fault diagnosis method with high generalizability under variable working conditions	107
Structural health monitoring using wireless smart sensor network – An overview	105
Deep representation clustering-based fault diagnosis method with unsupervised data applied to rotating machinery	103
Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks	103
A bio-inspired isolator based on characteristics of quasi-zero stiffness and bird multi-layer neck	102
Design and experimental investigation of ultra-low frequency vibration isolation during neonatal transport	102
Metric-based meta-learning model for few-shot fault diagnosis under multiple limited data conditions	100
Blind filters based on envelope spectrum sparsity indicators for bearing and gear vibration-based condition monitoring	100
A novel bio-inspired multi-joint anti-vibration structure and its nonlinear HSLDS properties	99
A semi-active suspension using a magnetorheological damper with nonlinear negative-stiffness component	98
Data synthesis using deep feature enhanced generative adversarial networks for rolling bearing imbalanced fault diagnosis	98
Reliability of response region: A novel mechanism in visual tracking by edge computing for IIoT environments	97
Vibration feature extraction using signal processing techniques for structural health monitoring: A review	97
Practical framework of Gini index in the application of machinery fault feature extraction	96
A theory for bistable vibration isolators	94
A review on the application of blind deconvolution in machinery fault diagnosis	93
Rolling element bearing diagnosis based on singular value decomposition and composite squared envelope spectrum	93
Damage localization in plate-like structures using time-varying feature and one-dimensional convolutional neural network	91
A novel method based on meta-learning for bearing fault diagnosis with small sample learning under different working conditions	89
A novel model with the ability of few-shot learning and quick updating for intelligent fault diagnosis	88
Increase of quasi-zero stiffness region using two pairs of oblique springs	88
Precise cutterhead torque prediction for shield tunneling machines using a novel hybrid deep neural network	88
A novel nonlinear mechanical oscillator and its application in vibration isolation and energy harvesting	85
Skidding dynamic performance of rolling bearing with cage flexibility under accelerating conditions	85
Asynchronous fault detection filtering for piecewise homogenous Markov jump linear systems via a dual hidden Markov model	85
A novel Fast Entrogram and its applications in rolling bearing fault diagnosis	84
Structural Health Monitoring using deep learning with optimal finite element model generated data	84
On the application of domain adaptation in structural health monitoring	83
Subband averaging kurtogram with dual-tree complex wavelet packet transform for rotating machinery fault diagnosis	83
Data management techniques for Internet of Things	82
Improved Envelope Spectrum via Feature Optimisation-gram (IESFOgram): A novel tool for rolling element bearing diagnostics under non-stationary operating conditions	82
Response time of magnetorheological dampers to current inputs in a semi-active suspension system: Modeling, control and sensitivity analysis	81

Enhancing energy harvesting in low-frequency rotational motion by a quad-stable energy harvester with time-varying potential wells	81
An improved variational mode decomposition method based on particle swarm optimization for leak detection of liquid pipelines	81
Transient wave-based methods for anomaly detection in fluid pipes: A review	80
Imbalanced fault diagnosis of rolling bearing using improved MsR-GAN and feature enhancement-driven CapsNet	80
Machine vision based condition monitoring and fault diagnosis of machine tools using information from machined surface texture: A review	79