Reliability Engineering & System Safety

Papers
(The H4-Index of Reliability Engineering & System Safety is 73. 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 2020-11-01 to 2024-11-01.)
ArticleCitations
Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice272
Machine learning for reliability engineering and safety applications: Review of current status and future opportunities232
Intelligent fault diagnosis of machinery using digital twin-assisted deep transfer learning207
Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry202
Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries197
A dual-LSTM framework combining change point detection and remaining useful life prediction196
Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network186
A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings177
Prediction of remaining useful life based on bidirectional gated recurrent unit with temporal self-attention mechanism177
Risk assessment of the operations of maritime autonomous surface ships155
Random forests for global sensitivity analysis: A selective review147
A Big Data Analytics Method for the Evaluation of Ship - Ship Collision Risk reflecting Hydrometeorological Conditions133
Prognostics and health management: A review from the perspectives of design, development and decision131
Fault diagnosis based on extremely randomized trees in wireless sensor networks130
Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework126
An analysis of factors affecting the severity of marine accidents124
Health status assessment and remaining useful life prediction of aero-engine based on BiGRU and MMoE124
Support vector machine in structural reliability analysis: A review121
Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles120
Resilience analysis of maritime transportation systems based on importance measures118
Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction118
Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture117
Remaining useful life prediction and predictive maintenance strategies for multi-state manufacturing systems considering functional dependence113
Hierarchical attention graph convolutional network to fuse multi-sensor signals for remaining useful life prediction113
Fusing physics-based and deep learning models for prognostics112
Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing111
Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions110
Assessment of failure rates and reliability of floating offshore wind turbines109
Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings107
Remaining useful life estimation of Lithium-ion battery based on interacting multiple model particle filter and support vector regression107
Bayesian network modeling of accident investigation reports for aviation safety assessment105
Remaining Useful Life Prediction of Lithium-ion Batteries Based on Wiener Process Under Time-Varying Temperature Condition104
Life prediction of lithium-ion batteries based on stacked denoising autoencoders98
An AIS-based deep learning framework for regional ship behavior prediction96
Intelligent fault identification of hydraulic pump using deep adaptive normalized CNN and synchrosqueezed wavelet transform94
An adaptive remaining useful life prediction approach for single battery with unlabeled small sample data and parameter uncertainty94
Machine learning-based methods in structural reliability analysis: A review92
Infrastructure resilience curves: Performance measures and summary metrics91
Long short-term memory network with Bayesian optimization for health prognostics of lithium-ion batteries based on partial incremental capacity analysis91
Resilience evaluation methodology of engineering systems with dynamic-Bayesian-network-based degradation and maintenance90
Modelling and estimation of system reliability under dynamic operating environments and lifetime ordering constraints90
Remaining useful life prediction based on a multi-sensor data fusion model89
Joint optimization of condition-based and age-based replacement policy and inventory policy for a two-unit series system88
Anomaly detection and diagnosis for wind turbines using long short-term memory-based stacked denoising autoencoders and XGBoost87
A generalized remaining useful life prediction method for complex systems based on composite health indicator87
A predictive analytics method for maritime traffic flow complexity estimation in inland waterways86
Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges86
Vulnerability of bridges to individual and multiple hazards- floods and earthquakes84
2MNet: Multi-sensor and multi-scale model toward accurate fault diagnosis of rolling bearing84
Blockchain-based decentralized federated transfer learning methodology for collaborative machinery fault diagnosis84
Remaining useful life estimation using deep metric transfer learning for kernel regression82
Spatial patterns and characteristics of global maritime accidents82
FGDAE: A new machinery anomaly detection method towards complex operating conditions82
Prediction of remaining useful life of multi-stage aero-engine based on clustering and LSTM fusion82
Review of techniques and challenges of human and organizational factors analysis in maritime transportation81
An integrated dynamic ship risk model based on Bayesian Networks and Evidential Reasoning81
Data-driven Bayesian network for risk analysis of global maritime accidents81
Degradation modeling and remaining useful life prediction for dependent competing failure processes80
Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks79
Towards a Convolutional Neural Network model for classifying regional ship collision risk levels for waterway risk analysis77
Quantitative analysis for resilience-based urban rail systems: A hybrid knowledge-based and data-driven approach76
Bayesian network model for buried gas pipeline failure analysis caused by corrosion and external interference75
Dynamic mission abort policy for systems operating in a controllable environment with self-healing mechanism75
Machine learning based water pipe failure prediction: The effects of engineering, geology, climate and socio-economic factors75
A prognostic driven predictive maintenance framework based on Bayesian deep learning75
Deep imbalanced domain adaptation for transfer learning fault diagnosis of bearings under multiple working conditions75
A variational local weighted deep sub-domain adaptation network for remaining useful life prediction facing cross-domain condition75
Fault prediction of bearings based on LSTM and statistical process analysis75
Sustainable manufacturing, maintenance policies, prognostics and health management: A literature review75
A hybrid approach based on decomposition algorithm and neural network for remaining useful life prediction of lithium-ion battery74
An integrated multi-head dual sparse self-attention network for remaining useful life prediction73
Federated multi-source domain adversarial adaptation framework for machinery fault diagnosis with data privacy73
Time-dependent reliability-based optimization for structural-topological configuration design under convex-bounded uncertain modeling73
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