On the public citation graph
Estimation of Bearing Remaining Useful Life Based on Multiscale Convolutional Neural Network
0 signed · 746 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/qre.1609openalex-snapshot
A Bayesian Approach to Condition Monitoring with Imperfect Inspections
inferredcites →https://doi.org/10.1006/mssp.1998.0183openalex-snapshot
Adaptive prognostics for rolling element bearing condition
inferredcites →https://doi.org/10.1007/978-3-319-32025-0_14openalex-snapshot
Deep Convolutional Neural Network Based Regression Approach for Estimation of Remaining Useful Life
inferredcites →https://doi.org/10.1016/j.cirp.2016.04.072openalex-snapshot
Design of deep convolutional neural network architectures for automated feature extraction in industrial inspection
inferredcites →https://doi.org/10.1016/j.dsp.2013.12.010openalex-snapshot
Condition assessment for the performance degradation of bearing based on a combinatorial feature extraction method
inferredcites →https://doi.org/10.1016/j.ejor.2010.11.018openalex-snapshot
Remaining useful life estimation – A review on the statistical data driven approaches
inferredcites →https://doi.org/10.1016/j.ejor.2014.11.029openalex-snapshot
Condition-based maintenance using the inverse Gaussian degradation model
inferredcites →https://doi.org/10.1016/j.eswa.2010.08.049openalex-snapshot
Application of relevance vector machine and survival probability to machine degradation assessment
inferredcites →https://doi.org/10.1016/j.ijfatigue.2015.05.017openalex-snapshot
Sequential Monte-Carlo sampling based on a committee of artificial neural networks for posterior state estimation and residual lifetime prediction
inferredcites →https://doi.org/10.1016/j.jsv.2016.05.027openalex-snapshot
Convolutional Neural Network Based Fault Detection for Rotating Machinery
inferredcites →https://doi.org/10.1016/j.jsv.2016.10.043openalex-snapshot
Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
inferredcites →https://doi.org/10.1016/j.measurement.2016.07.054openalex-snapshot
Hierarchical adaptive deep convolution neural network and its application to bearing fault diagnosis
inferredcites →https://doi.org/10.1016/j.neucom.2017.02.045openalex-snapshot
A recurrent neural network based health indicator for remaining useful life prediction of bearings
inferredcites →https://doi.org/10.1016/j.renene.2010.05.012openalex-snapshot
Wind turbine fault diagnosis based on Morlet wavelet transformation and Wigner-Ville distribution
inferredcites →https://doi.org/10.1016/j.ress.2010.12.023openalex-snapshot
Condition based maintenance optimization for multi-component systems using proportional hazards model
inferredcites →https://doi.org/10.1016/j.ymssp.2005.11.008openalex-snapshot
Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods
inferredcites →https://doi.org/10.1016/j.ymssp.2011.10.019openalex-snapshot
A generic probabilistic framework for structural health prognostics and uncertainty management
inferredcites →https://doi.org/10.1016/j.ymssp.2016.07.039openalex-snapshot
An integrated Gaussian process regression for prediction of remaining useful life of slow speed bearings based on acoustic emission
inferredcites →https://doi.org/10.1016/j.ymssp.2017.06.004openalex-snapshot
Two novel mixed effects models for prognostics of rolling element bearings
inferredcites →https://doi.org/10.1016/j.ymssp.2017.07.015openalex-snapshot
Brownian motion with adaptive drift for remaining useful life prediction: Revisited
inferredcites →https://doi.org/10.1016/j.ymssp.2017.11.016openalex-snapshot
Machinery health prognostics: A systematic review from data acquisition to RUL prediction
inferredcites →https://doi.org/10.1080/00031305.1983.10483087openalex-snapshot
A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation
inferredcites →https://doi.org/10.1080/07408170590929018openalex-snapshot
Residual-life distributions from component degradation signals: A Bayesian approach
inferredcites →https://doi.org/10.1080/0740817x.2012.706376openalex-snapshot
Condition monitoring and remaining useful life prediction using degradation signals: revisited
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cvpr.2014.244openalex-snapshot
Deep Learning Face Representation from Predicting 10,000 Classes
inferredcites →https://doi.org/10.1109/phm.2008.4711423openalex-snapshot
Data driven prognostics using a Kalman filter ensemble of neural network models
inferredcites →https://doi.org/10.1109/tie.2004.824875openalex-snapshot
Residual Life Predictions From Vibration-Based Degradation Signals: A Neural Network Approach
inferredcites →https://doi.org/10.1109/tie.2010.2098369openalex-snapshot
Machine Condition Prediction Based on Adaptive Neuro–Fuzzy and High-Order Particle Filtering
inferredcites →https://doi.org/10.1109/tie.2016.2582729openalex-snapshot
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/tii.2016.2645238openalex-snapshot
Dislocated Time Series Convolutional Neural Architecture: An Intelligent Fault Diagnosis Approach for Electric Machine
inferredcites →https://doi.org/10.1109/tii.2017.2684821openalex-snapshot
RUL Prediction of Deteriorating Products Using an Adaptive Wiener Process Model
inferredcites →https://doi.org/10.1109/tim.2017.2674738openalex-snapshot
Energy-Fluctuated Multiscale Feature Learning With Deep ConvNet for Intelligent Spindle Bearing Fault Diagnosis
inferredcites →https://doi.org/10.1109/tr.2013.2285318openalex-snapshot
Remaining Useful Life Estimation in Rolling Bearings Utilizing Data-Driven Probabilistic E-Support Vectors Regression
inferredcites →https://doi.org/10.1109/tr.2017.2739126openalex-snapshot
Statistical Modeling of Bearing Degradation Signals
inferredcites →https://doi.org/10.1109/tsmc.2017.2697842openalex-snapshot
Using Deep Learning-Based Approach to Predict Remaining Useful Life of Rotating Components
inferredcites →https://doi.org/10.1137/0515056openalex-snapshot
Decomposition of Hardy Functions into Square Integrable Wavelets of Constant Shape
inferredcites →https://doi.org/10.14445/22315381/ijett-v12p282openalex-snapshot
Image Fusion Using LEP Filtering and Bilinear Interpolation
inferredcites →https://doi.org/10.3390/s17020414openalex-snapshot
An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4351206openalex-extracted
Application of Multi-Scale Convolutional Neural Networks and Extreme Learning Machine in Mechanical Fault Diagnosis
inferred← citeshttps://doi.org/10.1002/9781119865728.ch10openalex-snapshot
Artificial Intelligence and Machine Learning‐Based Manufacturing and Drug Product Marketing
inferred← citeshttps://doi.org/10.1002/cjce.25004openalex-snapshot
Fault diagnosis of complex chemical process based on multi‐scale ADCRC feature learning
inferred← citeshttps://doi.org/10.1002/qre.2651openalex-snapshot
Remaining useful life prediction via a variational autoencoder and a time‐window‐based sequence neural network
inferred← citeshttps://doi.org/10.1002/qre.2947openalex-snapshot
Diagnostics and prognostics for complex systems: A review of methods and challenges
inferred← citeshttps://doi.org/10.1002/qre.3151openalex-snapshot
Remaining useful life prediction using composite health index and hybrid LSTM‐SVR model
inferred← citeshttps://doi.org/10.1002/qre.3261openalex-snapshot
Transfer learning based deep learning model and control chart for bearing useful life prediction
inferred← citeshttps://doi.org/10.1002/qre.3308openalex-snapshot
Remaining useful life prediction of rolling bearings based on Bayesian neural network and uncertainty quantification
inferred← citeshttps://doi.org/10.1002/qre.3615openalex-snapshot
Degradation index‐based prediction for remaining useful life using multivariate sensor data
inferred← citeshttps://doi.org/10.1002/qre.3630openalex-snapshot
A hybrid reliability assessment method based on health index construction and reliability modeling for rolling bearing
inferred← citeshttps://doi.org/10.1002/qre.3659openalex-snapshot
A bivariate dependent degradation model based on artificial neural network supported stochastic process and Copula function
inferred← citeshttps://doi.org/10.1007/978-3-030-57745-2_122openalex-snapshot
Remaining Useful Life Prediction for Bearings of Shearer Rocker Transmission Parts Based on Internet of Things
inferred← citeshttps://doi.org/10.1007/978-3-030-62466-8_32openalex-snapshot
Reasoning Engine for Support Maintenance
inferred← citeshttps://doi.org/10.1007/978-3-030-78621-2_49openalex-snapshot
Research on Life Prediction Model of Field Seismic Equipment Based on IFA-RVM Algorithm
inferred← citeshttps://doi.org/10.1007/978-3-031-00978-5_5openalex-snapshot
A Proposal for Improving Remaining Useful Life Prediction in Industrial Systems: A Deep Learning Approach
inferred← citeshttps://doi.org/10.1007/978-3-031-23615-0_33openalex-snapshot
Evaluation of AutoML Tools for Manufacturing Applications
inferred← citeshttps://doi.org/10.1007/978-3-031-26193-0_33openalex-snapshot
Temporal Convolutional Network with Attention Mechanism for Bearing Remaining Useful Life Prediction
inferred← citeshttps://doi.org/10.1007/978-3-031-47724-9_4openalex-snapshot
Wind Turbine Data-Driven Intelligent Fault Detection
inferred← citeshttps://doi.org/10.1007/978-3-031-78398-2_1openalex-snapshot
Time-Series Representation Learning via Heterogeneous Spatial-Temporal Contrasting for Remaining Useful Life Prediction
inferred← citeshttps://doi.org/10.1007/978-3-031-87837-4_15openalex-snapshot
Predictive Maintenance in Industry 5.0: A Comparative Study of Various Deep Learning Models for Remaining Useful Life Prediction of Turbofan Engines
inferred← citeshttps://doi.org/10.1007/978-3-032-10150-1_27openalex-snapshot
Integration of Deep Learning Techniques with the Bees Algorithm to Predict the Remaining Useful Life of Components for Remanufacturing
inferred← citeshttps://doi.org/10.1007/978-981-16-9131-7_5openalex-snapshot
Data-Driven RUL Prediction
inferred← citeshttps://doi.org/10.1007/978-981-19-3266-3_34openalex-snapshot
Prediction of Remaining Useful Life (RUL) of Bearing Using Exponential Degradation Model
inferred← citeshttps://doi.org/10.1007/978-981-19-6613-2_502openalex-snapshot
Multi-output Structure Combined with Separable Convolutional GRU Model for Aero-Engine RUL Prediction
inferred← citeshttps://doi.org/10.1007/978-981-95-8988-3_17openalex-snapshot
Remaining Useful Life Prediction for Bearings in Highway Machinery Equipment Based on ICEEMDAN-ISOMAP-DCLSTM Framework
inferred← citeshttps://doi.org/10.1007/978-981-96-2200-9_7openalex-snapshot
A Degradation Modeling Method Based on Gamma Process with Artificial Neural Network Utilizing Two Types of Testing Data
inferred← citeshttps://doi.org/10.1007/978-981-96-3592-4_45openalex-snapshot
Data-Driven Remaining Useful Life Prediction for Maritime Equipment: A Literature Survey
inferred← citeshttps://doi.org/10.1007/978-981-96-6732-1_24openalex-snapshot
Monotonicity Score-Based Remaining Useful Life Prediction of Bearing Using Gaussian Process Regression
inferred← citeshttps://doi.org/10.1007/978-981-96-9697-0_80openalex-snapshot
Coupler Life Prediction Based on LSTM
inferred← citeshttps://doi.org/10.1007/978-981-96-9921-6_13openalex-snapshot
Bearing Remaining Useful Life Prediction Based on Multi-scale Feature Extraction and Convolutional Attention Mechanism
inferred← citeshttps://doi.org/10.1007/978-981-97-4700-9_27openalex-snapshot
Artificial Intelligence-Enabled Predictive Maintenance for the Resilient Manufacturing: Current Applications and Challenges
inferred← citeshttps://doi.org/10.1007/s00170-022-09198-wopenalex-snapshot
A novel hybrid model integrating residual structure and bi-directional long short-term memory network for tool wear monitoring
inferred← citeshttps://doi.org/10.1007/s00170-022-09452-1openalex-snapshot
Transfer fault prognostic for rolling bearings across different working conditions: a domain adversarial perspective
inferred← citeshttps://doi.org/10.1007/s00170-025-17139-6openalex-snapshot
Remaining useful life prediction of rolling bearings via wavelet feature fusion and LSTM networks
inferred← citeshttps://doi.org/10.1007/s00170-026-17891-3openalex-snapshot
Fatigue failure mechanisms and multi-factor coupled modeling of roller bearings: a review
inferred← citeshttps://doi.org/10.1007/s00202-024-02411-xopenalex-snapshot
Study of bearing currents in induction machine: diagnostic possibilities, fault detection, and prediction
inferred← citeshttps://doi.org/10.1007/s00500-022-06755-zopenalex-snapshot
RETRACTED ARTICLE: Machine health surveillance system by using deep learning sparse autoencoder
inferred← citeshttps://doi.org/10.1007/s00500-022-07625-4openalex-snapshot
A deep learning-based conditional system health index method to reduce the uncertainty of remaining useful life prediction
inferred← citeshttps://doi.org/10.1007/s00500-025-10937-wopenalex-snapshot
CARLE: a hybrid deep-shallow learning framework for robust and explainable RUL estimation of rolling element bearings
inferred← citeshttps://doi.org/10.1007/s00521-021-05976-xopenalex-snapshot
A data-driven approach based on deep neural networks for lithium-ion battery prognostics
inferred← citeshttps://doi.org/10.1007/s00521-022-07322-1openalex-snapshot
A prediction-based cycle life test optimization method for cross-formula batteries using instance transfer and variable-length-input deep learning model
inferred← citeshttps://doi.org/10.1007/s10483-022-2926-9openalex-snapshot
Local parameter identification with neural ordinary differential equations
inferred← citeshttps://doi.org/10.1007/s10489-021-02503-2openalex-snapshot
Convolutional neural network based on attention mechanism and Bi-LSTM for bearing remaining life prediction
inferred← citeshttps://doi.org/10.1007/s10489-022-03670-6openalex-snapshot
Wasserstein distance based multi-scale adversarial domain adaptation method for remaining useful life prediction
inferred← citeshttps://doi.org/10.1007/s10489-023-04855-3openalex-snapshot
A hybrid-driven remaining useful life prediction method combining asymmetric dual-channel autoencoder and nonlinear Wiener process
inferred← citeshttps://doi.org/10.1007/s10489-025-07007-xopenalex-snapshot
A remaining useful life prediction method for rotating machinery based on trend encoding and multi-scale spatio-temporal feature fusion
inferred← citeshttps://doi.org/10.1007/s10845-022-01916-1openalex-snapshot
A dynamic mode decomposition based deep learning technique for prognostics
inferred← citeshttps://doi.org/10.1007/s10845-022-02015-xopenalex-snapshot
A novel feature-fusion-based end-to-end approach for remaining useful life prediction
inferred← citeshttps://doi.org/10.1007/s10845-023-02215-zopenalex-snapshot
Towards prognostic generalization: a domain conditional invariance and specificity disentanglement network for remaining useful life prediction
inferred← citeshttps://doi.org/10.1007/s10845-023-02264-4openalex-snapshot
A novel transfer learning approach based on deep degradation feature adaptive alignment for remaining useful life prediction with multi-condition data
inferred← citeshttps://doi.org/10.1007/s10845-024-02386-3openalex-snapshot
A transfer regression network-based adaptive calibration method for remaining useful life prediction considering individual discrepancies in the degradation process of machinery
inferred← citeshttps://doi.org/10.1007/s10845-024-02399-yopenalex-snapshot
Remaining useful life prediction based on parallel multi-scale feature fusion network
inferred← citeshttps://doi.org/10.1007/s10845-024-02536-7openalex-snapshot
Large scale foundation models for intelligent manufacturing applications: a survey
inferred← citeshttps://doi.org/10.1007/s10916-020-01676-6openalex-snapshot
Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolutional Neural Network
inferred← citeshttps://doi.org/10.1007/s10994-023-06305-0openalex-snapshot
Diverse and consistent multi-view networks for semi-supervised regression
inferred← citeshttps://doi.org/10.1007/s11063-022-11032-zopenalex-snapshot
Global Attention-Based Graph Neural Networks for Node Classification
inferred← citeshttps://doi.org/10.1007/s11424-025-4001-2openalex-snapshot
Cross-Sensor Generative Self-Supervised Learning Network for Fault Detection Under Few Samples
inferred← citeshttps://doi.org/10.1007/s11760-024-03534-1openalex-snapshot
SRCAE-STCBiGRU: a fused deep learning model for remaining useful life prediction of rolling bearings
inferred← citeshttps://doi.org/10.1007/s11760-026-05117-8openalex-snapshot
DARD-BiLSTM with gated fusion for predicting the remaining useful life of turbofan engines
inferred← citeshttps://doi.org/10.1007/s12206-020-1202-4openalex-snapshot
Remaining useful life prediction of planet bearings based on conditional deep recurrent generative adversarial network and action discovery
inferred← citeshttps://doi.org/10.1007/s12206-021-0707-9openalex-snapshot
A novel intelligent fault diagnosis method based on dual convolutional neural network with multi-level information fusion
inferred← citeshttps://doi.org/10.1007/s12206-021-1103-1openalex-snapshot
An effective residual life prediction method of rolling element bearings based on degradation trajectory analysis
inferred← citeshttps://doi.org/10.1007/s12206-021-1109-8openalex-snapshot
Data-driven prognostics method for turbofan engine degradation using hybrid deep neural network
inferred← citeshttps://doi.org/10.1007/s12206-024-0402-8openalex-snapshot
LSTM-based deep learning approach for remaining useful life prediction of rolling bearing using proposed C-MMPE feature
inferred← citeshttps://doi.org/10.1007/s13042-024-02498-5openalex-snapshot
A hybrid optimized approaches for ball bearing state prognosis for effective decision making
inferred← citeshttps://doi.org/10.1007/s13198-023-01979-0openalex-snapshot
Adaptive remaining useful life prediction framework with stochastic failure threshold for experimental bearings with different lifetimes under contaminated condition
inferred← citeshttps://doi.org/10.1007/s40314-021-01752-8openalex-snapshot
Computational adaptive multivariable degradation model for improving the remaining useful life prediction in industrial systems
inferred← citeshttps://doi.org/10.1007/s40430-020-02563-4openalex-snapshot
A new Wasserstein distance- and cumulative sum-dependent health indicator and its application in prediction of remaining useful life of bearing
inferred← citeshttps://doi.org/10.1007/s40430-022-03638-0openalex-snapshot
Remaining useful life prediction for rolling bearings based on similarity feature fusion and convolutional neural network
inferred← citeshttps://doi.org/10.1007/s40430-023-04062-8openalex-snapshot
RUL prediction based on GAM–CNN for rotating machinery
inferred← citeshttps://doi.org/10.1007/s40430-026-06511-6openalex-snapshot
Ensemble learning-based fatigue life prediction method for controllable pitch propeller oil pipe system under small-sample conditions
inferred← citeshttps://doi.org/10.1007/s42417-025-02322-6openalex-snapshot
A Review of Various Fault Diagnosis and RUL Estimation Techniques for Predictive Maintenance in Industrial Rotating Machinery
inferred← citeshttps://doi.org/10.1007/s42835-024-02036-xopenalex-snapshot
Self-attention Mechanism Network Integrating Spatio-Temporal Feature Extraction for Remaining Useful Life Prediction
inferred← citeshttps://doi.org/10.1007/s43684-024-00088-4openalex-snapshot
Enhanced bearing RUL prediction based on dynamic temporal attention and mixed MLP
inferred← citeshttps://doi.org/10.1016/b978-0-323-99989-2.00001-3openalex-snapshot
Fault diagnosis and prognosis driven by deep transfer learning
inferred← citeshttps://doi.org/10.1016/j.aei.2021.101396openalex-snapshot
A multi-head neural network with unsymmetrical constraints for remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.aei.2023.101966openalex-snapshot
A new convolutional dual-channel Transformer network with time window concatenation for remaining useful life prediction of rolling bearings
inferred← citeshttps://doi.org/10.1016/j.aei.2023.102014openalex-snapshot
Hybrid scheme through read-first-LSTM encoder-decoder and broad learning system for bearings degradation monitoring and remaining useful life estimation
inferred← citeshttps://doi.org/10.1016/j.aei.2023.102247openalex-snapshot
Conditional variational transformer for bearing remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.aei.2024.102524openalex-snapshot
Advancing RUL prediction in mechanical systems: A hybrid deep learning approach utilizing non-full lifecycle data
inferred← citeshttps://doi.org/10.1016/j.aei.2024.102767openalex-snapshot
A prognostic model for multi-stage degraded equipment under zero life label combining CDBN and Bayesian bidirectional GRU
inferred← citeshttps://doi.org/10.1016/j.aei.2024.103053openalex-snapshot
A novel multi-task learning framework with fault mode feature separation for remaining useful life estimation of mechanical systems
inferred← citeshttps://doi.org/10.1016/j.aei.2024.103077openalex-snapshot
Neural ODE powered model for bearing remaining useful life predictions with intra- and inter-domain shifts
inferred← citeshttps://doi.org/10.1016/j.aei.2025.103471openalex-snapshot
Physics-informed CGAN and multi-scale attention CNN for pipeline leakage diagnosis under imbalanced data
inferred← citeshttps://doi.org/10.1016/j.aei.2025.104069openalex-snapshot
Online learning for remaining useful life prediction via a novel SAC algorithm with hierarchical storage and experience mixing
inferred← citeshttps://doi.org/10.1016/j.aei.2026.105232openalex-snapshot
Toward accurate remaining useful life and state of health estimation using reinforced graph-based physics-informed neural networks enhanced with dynamic weights
inferred← citeshttps://doi.org/10.1016/j.aej.2026.03.044openalex-snapshot
Hybrid wavelet transform and deep learning method for fault diagnosis of transformer vibration signals
inferred← citeshttps://doi.org/10.1016/j.amc.2021.126757openalex-snapshot
Reliability estimation from two types of accelerated testing data based on an artificial neural network supported Wiener process
inferred← citeshttps://doi.org/10.1016/j.apm.2023.05.042openalex-snapshot
A wavelet neural network informed by time-domain signal preprocessing for bearing remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.asoc.2019.105919openalex-snapshot
A novel deep learning method based on attention mechanism for bearing remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.asoc.2021.108401openalex-snapshot
Robust state-of-charge estimation of Li-ion batteries based on multichannel convolutional and bidirectional recurrent neural networks
inferred← citeshttps://doi.org/10.1016/j.asoc.2022.109271openalex-snapshot
Deep imbalanced regression using cost-sensitive learning and deep feature transfer for bearing remaining useful life estimation
inferred← citeshttps://doi.org/10.1016/j.asoc.2022.109763openalex-snapshot
A bearing prognosis framework based on deep wavelet extreme learning machine and particle filtering
inferred← citeshttps://doi.org/10.1016/j.asoc.2023.110044openalex-snapshot
A reliability estimation method based on signal feature extraction and artificial neural network supported Wiener process with random effects
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.113067openalex-snapshot
Strategic integration of adaptive sampling and ensemble techniques in federated learning for aircraft engine remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.114003openalex-snapshot
Deep state space models for remaining useful life estimation
inferred← citeshttps://doi.org/10.1016/j.cie.2026.111996openalex-snapshot
A wavelet-constrained band attention neural network for physics-informed interpretable tool wear prediction
inferred← citeshttps://doi.org/10.1016/j.cnsns.2024.108411openalex-snapshot
ConvLSTM-based spatiotemporal and temporal processing models for chaotic vibration prediction of a microbeam
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2023.108745openalex-snapshot
A two-stage approach based on Bayesian deep learning for predicting remaining useful life of rolling element bearings
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2024.109853openalex-snapshot
Remaining useful life prediction method of bearings based on the interactive learning strategy
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2026.111023openalex-snapshot
Scalable decentralized prognostics for industrial systems under data heterogeneity
inferred← citeshttps://doi.org/10.1016/j.compind.2019.103182openalex-snapshot
An ensemble framework based on convolutional bi-directional LSTM with multiple time windows for remaining useful life estimation
inferred← citeshttps://doi.org/10.1016/j.compind.2023.103888openalex-snapshot
Trans-Lighter: A light-weight federated learning-based architecture for Remaining Useful Lifetime prediction
inferred← citeshttps://doi.org/10.1016/j.compind.2026.104482openalex-snapshot
Frequency-aware transferability analytics for few-shot deep domain-adversarial regression adaptation in remaining life prediction across different machines
inferred← citeshttps://doi.org/10.1016/j.compstruct.2023.116815openalex-snapshot
Non-destructive strength prediction of composite laminates utilizing deep learning and the stochastic finite element methods
inferred← citeshttps://doi.org/10.1016/j.conengprac.2021.104969openalex-snapshot
MSWR-LRCN: A new deep learning approach to remaining useful life estimation of bearings
inferred← citeshttps://doi.org/10.1016/j.conengprac.2023.105840openalex-snapshot
A change point detection integrated remaining useful life estimation model under variable operating conditions
inferred← citeshttps://doi.org/10.1016/j.dsp.2023.104197openalex-snapshot
SD2SDFNet: A novel deep fusion network based on statistical denoising and dual-dimension self-attention model for power transformer hybrid-space fault prognosis
inferred← citeshttps://doi.org/10.1016/j.egyr.2020.11.265openalex-snapshot
A hybrid prognostics approach for estimating remaining useful life of wind turbine bearings
inferred← citeshttps://doi.org/10.1016/j.enbuild.2021.110875openalex-snapshot
Fault prognosis of HVAC air handling unit and its components using hidden-semi Markov model and statistical process control
inferred← citeshttps://doi.org/10.1016/j.energy.2023.127747openalex-snapshot
Voltage-temperature aware thermal runaway alarming framework for electric vehicles via deep learning with attention mechanism in time-frequency domain
inferred← citeshttps://doi.org/10.1016/j.energy.2023.128442openalex-snapshot
A deep feature learning method for remaining useful life prediction of drilling pumps
inferred← citeshttps://doi.org/10.1016/j.engappai.2020.103753openalex-snapshot
Real-time prediction of process forces in milling operations using synchronized data fusion of simulation and sensor data
inferred← citeshttps://doi.org/10.1016/j.engappai.2020.103849openalex-snapshot
Remaining useful life estimation with multiple local similarities
inferred← citeshttps://doi.org/10.1016/j.engappai.2020.103936openalex-snapshot
Aircraft engines Remaining Useful Life prediction with an adaptive denoising online sequential Extreme Learning Machine
inferred← citeshttps://doi.org/10.1016/j.engappai.2021.104552openalex-snapshot
Artificial intelligence in prognostics and health management of engineering systems
inferred← citeshttps://doi.org/10.1016/j.engappai.2022.105712openalex-snapshot
A multi-model data-fusion based deep transfer learning for improved remaining useful life estimation for IIOT based systems
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107052openalex-snapshot
Attention gate guided multiscale recursive fusion strategy for deep neural network-based fault diagnosis
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.108161openalex-snapshot
A regularized constrained two-stream convolution augmented Transformer for aircraft engine remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.108285openalex-snapshot
A survey of deep learning-driven architecture for predictive maintenance
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.108308openalex-snapshot
Remaining useful life estimation of bearing via temporal convolutional networks enhanced by a gated convolutional unit
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.108813openalex-snapshot
Remaining useful life prediction of machinery based on improved Sample Convolution and Interaction Network
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.111070openalex-snapshot
Rolling bearings remaining useful life estimation using digital twin and physics-informed methods with uncertainty quantification
inferred← citeshttps://doi.org/10.1016/j.engappai.2026.114614openalex-snapshot
A bilevel meta-task correlation network for bearings remaining useful life prediction with limited data
inferred← citeshttps://doi.org/10.1016/j.engappai.2026.116359openalex-snapshot
Frequency–spatial feature learning with spectrally guided data augmentation for submarine cable fault detection under data scarcity
inferred← citeshttps://doi.org/10.1016/j.engfailanal.2023.107125openalex-snapshot
Estimating remaining useful life of rotating machinery using relevance vector machine and deep learning network
inferred← citeshttps://doi.org/10.1016/j.engfailanal.2023.107815openalex-snapshot
Role of image feature enhancement in intelligent fault diagnosis for mechanical equipment: A review
inferred← citeshttps://doi.org/10.1016/j.est.2025.115575openalex-snapshot
Stat-of-charge estimation for lithium-ion batteries based on recurrent neural network: Current status and perspectives
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.117415openalex-snapshot
Joint training of a predictor network and a generative adversarial network for time series forecasting: A case study of bearing prognostics
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.121859openalex-snapshot
Bayesian gated-transformer model for risk-aware prediction of aero-engine remaining useful life
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.123930openalex-snapshot
Cost-sensitive learning considering label and feature distribution consistency: A novel perspective for health prognosis of rotating machinery with imbalanced data
inferred← citeshttps://doi.org/10.1016/j.flowmeasinst.2019.03.004openalex-snapshot
Development of a flow control valve with digital flow compensator
inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e26230openalex-snapshot
A reliability estimation method based on combination of failure mechanism and ANN supported wiener processes
inferred← citeshttps://doi.org/10.1016/j.ifacol.2020.12.2795openalex-snapshot
Gated Recurrent Unit Networks for Remaining Useful Life Prediction
inferred← citeshttps://doi.org/10.1016/j.ifacol.2022.07.444openalex-snapshot
Remaining Useful Life Estimation for Ball Bearings Using Feature Engineering and Extreme Learning Machine
inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103427openalex-snapshot
Interpretable prognostics with concept bottleneck models
inferred← citeshttps://doi.org/10.1016/j.ins.2020.12.032openalex-snapshot
Multiscale deep bidirectional gated recurrent neural networks based prognostic method for complex non-linear degradation systems
inferred← citeshttps://doi.org/10.1016/j.ins.2023.119795openalex-snapshot
Few-shot remaining useful life prediction based on meta-learning with deep sparse kernel network
inferred← citeshttps://doi.org/10.1016/j.isatra.2020.06.023openalex-snapshot
LSTM networks based on attention ordered neurons for gear remaining life prediction
inferred← citeshttps://doi.org/10.1016/j.isatra.2021.04.022openalex-snapshot
Intelligent vibration signal denoising method based on non-local fully convolutional neural network for rolling bearings
inferred← citeshttps://doi.org/10.1016/j.isatra.2022.01.031openalex-snapshot
Remaining Useful Life prediction of rolling bearings based on risk assessment and degradation state coefficient
inferred← citeshttps://doi.org/10.1016/j.isatra.2023.11.043openalex-snapshot
A new domain adaption residual separable convolutional neural network model for cross-domain remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.isatra.2023.12.031openalex-snapshot
Joint optimization of degradation assessment and remaining useful life prediction for bearings with temporal convolutional auto-encoder
inferred← citeshttps://doi.org/10.1016/j.isatra.2024.04.005openalex-snapshot
Intelligent condition monitoring with CNN and signal enhancement for undersampled signals
inferred← citeshttps://doi.org/10.1016/j.jii.2023.100444openalex-snapshot
Interaction models for remaining useful lifetime estimation
inferred← citeshttps://doi.org/10.1016/j.jmsy.2021.03.012openalex-snapshot
A novel deep convolutional neural network-bootstrap integrated method for RUL prediction of rolling bearing
inferred← citeshttps://doi.org/10.1016/j.jmsy.2021.03.024openalex-snapshot
Deep multi-scale adversarial network with attention: A novel domain adaptation method for intelligent fault diagnosis
inferred← citeshttps://doi.org/10.1016/j.jmsy.2022.05.010openalex-snapshot
Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods
inferred← citeshttps://doi.org/10.1016/j.jmsy.2023.04.002openalex-snapshot
A piecewise method for bearing remaining useful life estimation using temporal convolutional networks
inferred← citeshttps://doi.org/10.1016/j.jmsy.2023.07.007openalex-snapshot
Multi-scale one-dimensional convolution tool wear monitoring based on multi-model fusion learning skills
inferred← citeshttps://doi.org/10.1016/j.knosys.2021.107866openalex-snapshot
Generalized multiscale feature extraction for remaining useful life prediction of bearings with generative adversarial networks
inferred← citeshttps://doi.org/10.1016/j.knosys.2022.108958openalex-snapshot
Temporal convolution-based sorting feature repeat-explore network combining with multi-band information for remaining useful life estimation of equipment
inferred← citeshttps://doi.org/10.1016/j.knosys.2022.110199openalex-snapshot
Domain generalization via adversarial out-domain augmentation for remaining useful life prediction of bearings under unseen conditions
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110391openalex-snapshot
Deep transfer learning-based hierarchical adaptive remaining useful life prediction of bearings considering the correlation of multistage degradation
inferred← citeshttps://doi.org/10.1016/j.knosys.2024.111783openalex-snapshot
RETRACTED: Mixup domain adaptations for dynamic remaining useful life predictions
inferred← citeshttps://doi.org/10.1016/j.measurement.2019.04.039openalex-snapshot
HYGP-MSAM based model for slewing bearing residual useful life prediction
inferred← citeshttps://doi.org/10.1016/j.measurement.2019.107132openalex-snapshot
A multi-ensemble method based on deep auto-encoders for fault diagnosis of rolling bearings
inferred← citeshttps://doi.org/10.1016/j.measurement.2020.107929openalex-snapshot
Deep learning for prognostics and health management: State of the art, challenges, and opportunities
inferred← citeshttps://doi.org/10.1016/j.measurement.2020.108064openalex-snapshot
Degradation assessment of bearings with trend-reconstruct-based features selection and gated recurrent unit network
inferred← citeshttps://doi.org/10.1016/j.measurement.2020.108205openalex-snapshot
Long-term gear life prediction based on ordered neurons LSTM neural networks
inferred← citeshttps://doi.org/10.1016/j.measurement.2020.108753openalex-snapshot
An enhanced encoder–decoder framework for bearing remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.108969openalex-snapshot
A universal LPC health monitoring method for rolling element bearings with ADSCI feature
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.108973openalex-snapshot
A robust construction of normalized CNN for online intelligent condition monitoring of rolling bearings considering variable working conditions and sources
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.109090openalex-snapshot
Transfer remaining useful life estimation of bearing using depth-wise separable convolution recurrent network
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.109201openalex-snapshot
An online transfer learning-based remaining useful life prediction method of ball bearings
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.109642openalex-snapshot
A deep attention residual neural network-based remaining useful life prediction of machinery
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.110076openalex-snapshot
A novel health indicator based on hysteresis loop for health prediction of flight control systems
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.110276openalex-snapshot
Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective
inferred← citeshttps://doi.org/10.1016/j.measurement.2021.110633openalex-snapshot
A hybrid denoising model using deep learning and sparse representation with application in bearing weak fault diagnosis
inferred← citeshttps://doi.org/10.1016/j.measurement.2022.111125openalex-snapshot
Interactive dual adversarial neural network framework: An open-set domain adaptation intelligent fault diagnosis method of rotating machinery
inferred← citeshttps://doi.org/10.1016/j.measurement.2022.111424openalex-snapshot
Dual residual attention network for remaining useful life prediction of bearings
inferred← citeshttps://doi.org/10.1016/j.measurement.2022.111588openalex-snapshot
Optimization of dilated convolution networks with application in remaining useful life prediction of induction motors
inferred← citeshttps://doi.org/10.1016/j.measurement.2022.111803openalex-snapshot
Remaining useful life prediction of rolling bearing based on multi-head attention embedded Bi-LSTM network
inferred← citeshttps://doi.org/10.1016/j.measurement.2022.112313openalex-snapshot
A generalized degradation tendency tracking strategy for gearbox remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.measurement.2023.112600openalex-snapshot
Prediction of bearing remaining useful life based on DACN-ConvLSTM model
inferred← citeshttps://doi.org/10.1016/j.measurement.2024.114177openalex-snapshot
Method to enhance time series rolling fault prediction by deep fast Fourier convolution
inferred← citeshttps://doi.org/10.1016/j.measurement.2024.114242openalex-snapshot
Enhancing non-stationary feature learning for remaining useful life prediction of aero-engine under multiple operating conditions
inferred← citeshttps://doi.org/10.1016/j.measurement.2024.115012openalex-snapshot
Causal dilated Convolution-Based residual DenseNet with channel attention for RUL prediction of rolling bearings
inferred← citeshttps://doi.org/10.1016/j.measurement.2024.116152openalex-snapshot
A hybrid algorithm for predicting the remaining service life of hybrid bearings based on bidirectional feature extraction
inferred← citeshttps://doi.org/10.1016/j.measurement.2024.116411openalex-snapshot
A novel two-dimensional progressive domain adaptation framework for cross-domain remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.measurement.2024.116589openalex-snapshot
Feature learning for bearing prognostics: A comprehensive review of machine/deep learning methods, challenges, and opportunities
inferred← citeshttps://doi.org/10.1016/j.measurement.2026.122371openalex-snapshot
A function-space variational inference-based method for bearing RUL prediction and uncertainty quantification
inferred← citeshttps://doi.org/10.1016/j.measurement.2026.123030openalex-snapshot
Semantic calibration of statistical degradation descriptors for cross-condition bearing remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.mechmachtheory.2026.106364openalex-snapshot
ATSMR: A new matrix-based remaining useful life prediction method for roller bearing
inferred← citeshttps://doi.org/10.1016/j.mfglet.2023.08.037openalex-snapshot
Federated learning with network pruning and rebirth for remaining useful life prediction of engineering systems
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.10.064openalex-snapshot
Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery
inferred← citeshttps://doi.org/10.1016/j.neucom.2020.07.088openalex-snapshot
A comprehensive review on convolutional neural network in machine fault diagnosis
inferred← citeshttps://doi.org/10.1016/j.neucom.2020.09.021openalex-snapshot
An adaptive prognostics method for fusing CDBN and diffusion process: Application to bearing data
inferred← citeshttps://doi.org/10.1016/j.neucom.2021.04.048openalex-snapshot
Spatiotemporal non-negative projected convolutional network with bidirectional NMF and 3DCNN for remaining useful life estimation of bearings
inferred← citeshttps://doi.org/10.1016/j.neucom.2021.09.022openalex-snapshot
Attention-based sequence to sequence model for machine remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.129487openalex-snapshot
Dual-attention enhanced variational encoding for interpretable remaining useful life prediction
inferred← citeshttps://doi.org/10.1016/j.neucom.2026.133739openalex-snapshot
Spatio-temporal adaptive graph neural network for remaining useful life prediction with uncertainty estimation
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2020.108525openalex-snapshot
A deep supervised learning approach for condition-based maintenance of naval propulsion systems
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2021.110141openalex-snapshot
A novel RUL prognosis methodology of multilevel system with cascading failure: Subsea oil and gas transportation systems as a case study
inferred← citeshttps://doi.org/10.1016/j.procir.2021.11.260openalex-snapshot
Hybrid Approach for Onsite Monitoring and Anomaly Detection of Cutting Tool Life
inferred← citeshttps://doi.org/10.1016/j.procs.2022.12.241openalex-snapshot
Self-Attention Transformer-Based Architecture for Remaining Useful Life Estimation of Complex Machines
inferred← citeshttps://doi.org/10.1016/j.psep.2026.108865openalex-snapshot
MTFN: A multi-scale transformer fusion network for oil and gas pipeline leakage detection
showing the first 200 of 707 · page through all 707
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.