On the public citation graph

Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning

https://doi.org/10.3390/s19051088

0 signed · 358 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.

Claim with ORCID

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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1006/jsvi.2000.2864openalex-snapshot

FEATURE EXTRACTION BASED ON MORLET WAVELET AND ITS APPLICATION FOR MECHANICAL FAULT DIAGNOSIS

inferredcites →https://doi.org/10.1007/0-387-26325-x_33openalex-snapshot

A Soft Computing Based Approach Using Signal-To-Image Conversion for Computer Aided Medical Diagnosis (CAMD)

inferredcites →https://doi.org/10.1007/978-3-319-10590-1_53openalex-snapshot

Visualizing and Understanding Convolutional Networks

inferredcites →https://doi.org/10.1007/s10994-014-5456-xopenalex-snapshot

Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD)

inferredcites →https://doi.org/10.1007/s11082-016-0680-1openalex-snapshot

Multivariate outlier mining and regression feedback for 3D measurement improvement in opto-mechanical system

inferredcites →https://doi.org/10.1016/j.dss.2013.08.002openalex-snapshot

Sentiment classification: The contribution of ensemble learning

inferredcites →https://doi.org/10.1016/j.eswa.2010.12.095openalex-snapshot

EEMD method and WNN for fault diagnosis of locomotive roller bearings

inferredcites →https://doi.org/10.1016/j.eswa.2013.01.033openalex-snapshot

Fault diagnosis of rolling element bearing with intrinsic mode function of acoustic emission data using APF-KNN

inferredcites →https://doi.org/10.1016/j.jhydrol.2015.06.008openalex-snapshot

Flood hazard risk assessment model based on random forest

inferredcites →https://doi.org/10.1016/j.knosys.2015.06.017openalex-snapshot

Intelligent fault diagnosis of roller bearings with multivariable ensemble-based incremental support vector machine

inferredcites →https://doi.org/10.1016/j.knosys.2017.10.024openalex-snapshot

Intelligent fault diagnosis of rolling bearing using deep wavelet auto-encoder with extreme learning machine

inferredcites →https://doi.org/10.1016/j.measurement.2006.10.010openalex-snapshot

A fault diagnosis approach for roller bearing based on IMF envelope spectrum and SVM

inferredcites →https://doi.org/10.1016/j.measurement.2009.01.001openalex-snapshot

Signal feature extraction based on an improved EMD method

inferredcites →https://doi.org/10.1016/j.neucom.2016.11.056openalex-snapshot

CNN for saliency detection with low-level feature integration

inferredcites →https://doi.org/10.1016/j.ress.2017.11.021openalex-snapshot

Remaining useful life estimation in prognostics using deep convolution neural networks

inferredcites →https://doi.org/10.1016/j.ymssp.2006.06.010openalex-snapshot

Decision tree and PCA-based fault diagnosis of rotating machinery

inferredcites →https://doi.org/10.1016/j.ymssp.2016.09.010openalex-snapshot

Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines

inferredcites →https://doi.org/10.1016/j.ymssp.2017.09.026openalex-snapshot

A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders

inferredcites →https://doi.org/10.1016/j.ymssp.2018.02.016openalex-snapshot

Artificial intelligence for fault diagnosis of rotating machinery: A review

inferredcites →https://doi.org/10.1016/s0888-3270(03)00075-xopenalex-snapshot

Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography

inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot

Deep learning

inferredcites →https://doi.org/10.1080/00207721.2012.670290openalex-snapshot

An application of a discrete wavelet transform and a back-propagation neural network algorithm for fault diagnosis on single-circuit transmission line

inferredcites →https://doi.org/10.1088/0957-0233/26/11/115002openalex-snapshot

Rolling bearing fault diagnosis using an optimization deep belief network

inferredcites →https://doi.org/10.1109/21.97458openalex-snapshot

A survey of decision tree classifier methodology

inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot

Gradient-based learning applied to document recognition

inferredcites →https://doi.org/10.1109/61.796234openalex-snapshot

High-impedance fault detection utilizing a Morlet wavelet transform approach

inferredcites →https://doi.org/10.1109/access.2017.2728010openalex-snapshot

Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery

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/ijcnn.2011.6033589openalex-snapshot

Traffic sign recognition with multi-scale Convolutional Networks

inferredcites →https://doi.org/10.1109/ijcnn.2016.7727518openalex-snapshot

Fault analysis of High Speed Train with DBN hierarchical ensemble

inferredcites →https://doi.org/10.1109/isie.2014.6864914openalex-snapshot

Machine vision supported by artificial intelligence

inferredcites →https://doi.org/10.1109/lsp.2017.2713830openalex-snapshot

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

inferredcites →https://doi.org/10.1109/tia.2017.2661250openalex-snapshot

Deep Learning Based Approach for Bearing Fault Diagnosis

inferredcites →https://doi.org/10.1109/tie.2013.2273471openalex-snapshot

Motor Bearing Fault Diagnosis Using Trace Ratio Linear Discriminant Analysis

inferredcites →https://doi.org/10.1109/tie.2017.2774777openalex-snapshot

A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

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/tim.2017.2759418openalex-snapshot

Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning

inferredcites →https://doi.org/10.1109/tmech.2017.2728371openalex-snapshot

Fault Diagnosis for Rotating Machinery Using Multiple Sensors and Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/tpel.2016.2608842openalex-snapshot

A Data-Driven Fault Diagnosis Methodology in Three-Phase Inverters for PMSM Drive Systems

inferredcites →https://doi.org/10.1109/tsm.2017.2676245openalex-snapshot

A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes

inferredcites →https://doi.org/10.1109/tsmc.2016.2531692openalex-snapshot

Online Fault Diagnosis of Motor Bearing via Stochastic-Resonance-Based Adaptive Filter in an Embedded System

inferredcites →https://doi.org/10.1109/tsmc.2017.2754287openalex-snapshot

A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis

inferredcites →https://doi.org/10.1155/2017/5067651openalex-snapshot

Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings

inferredcites →https://doi.org/10.3390/s16060895openalex-snapshot

Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning

inferredcites →https://doi.org/10.3390/s16091509openalex-snapshot

Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis

inferredcites →https://doi.org/10.5545/sv-jme.2010.162openalex-snapshot

Signal Model-Based Fault Detection and Diagnosis for Induction Motors Using Features of Vibration Signal in Two-Dimension Domain

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.4092632openalex-extracted

inferred← citeshttps://doi.org/10.1002/9781394275519.ch14openalex-snapshot

Enhancing Error Prediction in Machineries through CNN and Random Forest Models Using IoT with Sensor Data Fusion

inferred← citeshttps://doi.org/10.1002/cpe.70166openalex-snapshot

Enhanced Quantum Ensemble Classification Algorithm With Shallow Circuit and Parallelism Mechanism

inferred← citeshttps://doi.org/10.1002/ldr.70518openalex-snapshot

Comparative Analysis of Regression and Classification‐Based Deep Learning and Machine Learning Models for Soil Erodibility Prediction

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/10.1007/978-3-030-70713-2_18openalex-snapshot

Detection of Cardiovascular Disease Using Ensemble Machine Learning Techniques

inferred← citeshttps://doi.org/10.1007/978-3-031-06794-5_29openalex-snapshot

Rolling Bearing Fault Diagnosis Method Based on Multiple Efficient Channel Attention Capsule Network

inferred← citeshttps://doi.org/10.1007/978-3-031-10450-3_1openalex-snapshot

Random Forest Based Deep Hybrid Architecture for Histopathological Breast Cancer Images Classification

inferred← citeshttps://doi.org/10.1007/978-3-031-29962-9_4openalex-snapshot

An Improved LeNet-5 Convolutional Neural Network Supporting Condition-Based Maintenance and Fault Diagnosis of Bearings

inferred← citeshttps://doi.org/10.1007/978-3-031-53036-4_15openalex-snapshot

Impact of EMG Signal Filters on Machine Learning Model Training: A Comparison with Clustering on Raw Signal

inferred← citeshttps://doi.org/10.1007/978-3-032-13803-3_4openalex-snapshot

Comparative Analysis of Bearing Fault Diagnosis Using Ensemble Machine Learning Techniques and Signal Processing

inferred← citeshttps://doi.org/10.1007/978-981-15-7106-0_14openalex-snapshot

Frequency Detection and Variation with Smart-Sensor Data Analysis Using Artificial Neural Network and Cloud Computing

inferred← citeshttps://doi.org/10.1007/978-981-16-3153-5_6openalex-snapshot

Deep Learning in Image Signal Processing for Minimal Method by Using Kernel DBN

inferred← citeshttps://doi.org/10.1007/978-981-16-9113-3_44openalex-snapshot

Handwritten Digit Recognition Using Very Deep Convolutional Neural Network

inferred← citeshttps://doi.org/10.1007/978-981-95-8098-9_13openalex-snapshot

Gated Recurrent Unit-Based Neural Network for Enhanced Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1007/978-981-96-7277-6_19openalex-snapshot

A Novel Deep Learning Method for Bearing Fault Diagnosis Based on FMD and Transformer

inferred← citeshttps://doi.org/10.1007/978-981-97-9037-1_23openalex-snapshot

Rolling Bearing Fault Classification: Multinomial Logistic Regression Approach for Enhanced Efficiency

inferred← citeshttps://doi.org/10.1007/978-981-97-9112-5_35openalex-snapshot

Condition Based Monitoring of Rolling Bearing by Naive Bayes Classifier

inferred← citeshttps://doi.org/10.1007/978-981-99-3925-1_21openalex-snapshot

The Motor Fault Diagnosis Based on Current Signal with Graph Attention Network

inferred← citeshttps://doi.org/10.1007/978-981-99-9562-2_18openalex-snapshot

Bearing Fault Diagnosis Using Machine Learning Models

inferred← citeshttps://doi.org/10.1007/s00170-019-04726-7openalex-snapshot

Rolling element bearing fault diagnosis for rotating machinery using vibration spectrum imaging and convolutional neural networks

inferred← citeshttps://doi.org/10.1007/s00170-019-04807-7openalex-snapshot

Milling chatter detection using scalogram and deep convolutional neural network

inferred← citeshttps://doi.org/10.1007/s00170-021-08392-6openalex-snapshot

Probabilistic bearing fault diagnosis using Gaussian process with tailored feature extraction

inferred← citeshttps://doi.org/10.1007/s00170-022-10792-1openalex-snapshot

A novel method for bearing fault diagnosis based on BiLSTM neural networks

inferred← citeshttps://doi.org/10.1007/s00170-023-12830-yopenalex-snapshot

AI-based inspection of the axes of machine tools

inferred← citeshttps://doi.org/10.1007/s00202-022-01523-6openalex-snapshot

Condition monitoring and fault detection of induction motor based on wavelet denoising with ensemble learning

inferred← citeshttps://doi.org/10.1007/s00521-022-07810-4openalex-snapshot

Interpretable Bayesian network abstraction for dimension reduction

inferred← citeshttps://doi.org/10.1007/s00521-023-08644-4openalex-snapshot

A new hybrid model of convolutional neural networks and hidden Markov chains for image classification

inferred← citeshttps://doi.org/10.1007/s00521-025-10998-wopenalex-snapshot

Electrical submersible pump fault diagnosis based on 2D transformation of vibration signals and transfer learning of image classification networks

inferred← citeshttps://doi.org/10.1007/s00784-020-03433-yopenalex-snapshot

Machine learning in prediction of genetic risk of nonsyndromic oral clefts in the Brazilian population

inferred← citeshttps://doi.org/10.1007/s10462-022-10283-5openalex-snapshot

A Survey on ensemble learning under the era of deep learning

inferred← citeshttps://doi.org/10.1007/s10489-022-04238-0openalex-snapshot

A new hyper-parameter optimization method for machine learning in fault classification

inferred← citeshttps://doi.org/10.1007/s10489-022-04342-1openalex-snapshot

An effective zero-shot learning approach for intelligent fault detection using 1D CNN

inferred← citeshttps://doi.org/10.1007/s10489-025-06920-5openalex-snapshot

Few-shot fault diagnosis of rolling bearing under variable conditions based on deep meta-transfer learning

inferred← citeshttps://doi.org/10.1007/s10845-020-01554-5openalex-snapshot

DAMER: a novel diagnosis aggregation method with evidential reasoning rule for bearing fault diagnosis

inferred← citeshttps://doi.org/10.1007/s10845-023-02176-3openalex-snapshot

Image deep learning in fault diagnosis of mechanical equipment

inferred← citeshttps://doi.org/10.1007/s11042-020-09534-wopenalex-snapshot

A fault diagnosis method of rolling bearing based on VMD Tsallis entropy and FCM clustering

inferred← citeshttps://doi.org/10.1007/s11071-020-06014-6openalex-snapshot

Permutation entropy-based 2D feature extraction for bearing fault diagnosis

inferred← citeshttps://doi.org/10.1007/s11668-025-02148-0openalex-snapshot

Weighted Aggregation Approach and Tree-Based Ensemble Technique for Anomaly Detection and Fault Severity Analysis in Gear Fault Diagnosis

inferred← citeshttps://doi.org/10.1007/s11740-026-01464-0openalex-snapshot

Hybrid EEMD-PCA and transformer-based deep learning approach for rotating bearing fault classification

inferred← citeshttps://doi.org/10.1007/s11760-022-02190-7openalex-snapshot

Imbalance domain adaptation network with adversarial learning for fault diagnosis of rolling bearing

inferred← citeshttps://doi.org/10.1007/s11760-026-05579-wopenalex-snapshot

Adaptive CNN-BO-XGBoost framework for traction motor fault diagnosis

inferred← citeshttps://doi.org/10.1007/s11831-025-10309-5openalex-snapshot

Advancements in Hybrid Machine Learning Models for Biomedical Disease Classification Using Integration of Hyperparameter-Tuning and Feature Selection Methodologies: A Comprehensive Review

inferred← citeshttps://doi.org/10.1007/s11831-025-10380-yopenalex-snapshot

Advances in Machine Learning and Deep Learning for Hormonal Disorder Diagnosis: an Exhaustive Review on PCOS, Thyroid, and Optimization Techniques

inferred← citeshttps://doi.org/10.1007/s12046-026-03235-0openalex-snapshot

Recent trends on bearing faults diagnosis of IM using vibration signal: a critical review

inferred← citeshttps://doi.org/10.1007/s12652-021-03177-xopenalex-snapshot

A bearing fault diagnosis model based on CNN with wide convolution kernels

inferred← citeshttps://doi.org/10.1007/s13198-025-03067-xopenalex-snapshot

Condition based monitoring of rolling bearing of rotating machines using intelligent fault classification

inferred← citeshttps://doi.org/10.1007/s13369-021-05527-5openalex-snapshot

Induction Motor Bearing Fault Classification Using Extreme Learning Machine Based on Power Features

inferred← citeshttps://doi.org/10.1007/s13369-022-06602-1openalex-snapshot

Prognostics of Aluminum Electrolytic Capacitors Based on Chained-SVR and 1D-CNN Ensemble Learning

inferred← citeshttps://doi.org/10.1007/s13369-025-10255-1openalex-snapshot

A Multi-stage Optimization Architecture for Effective Breast Cancer Diagnosis Based on Deep Neural Networks

inferred← citeshttps://doi.org/10.1007/s40430-020-02776-7openalex-snapshot

Denoising convolutional autoencoder configuration for condition monitoring of rotating machines

inferred← citeshttps://doi.org/10.1007/s40430-023-04344-1openalex-snapshot

Fault diagnosis for rolling bearing of road heading machine via SVDS-ICNN

inferred← citeshttps://doi.org/10.1007/s40430-026-06435-1openalex-snapshot

A dual-condition cost-sensitive optimization framework for intelligent bearing fault diagnosis

inferred← citeshttps://doi.org/10.1007/s40430-026-06913-6openalex-snapshot

Deep convolutional neural network for bearing fault diagnosis using noise-reduced vibration signals

inferred← citeshttps://doi.org/10.1007/s40435-026-02047-8openalex-snapshot

A robust deep learning framework for bearing fault diagnosis using residual shrinkage networks and signal denoising

inferred← citeshttps://doi.org/10.1007/s40747-022-00733-6openalex-snapshot

A wavelet convolutional capsule network with modified super resolution generative adversarial network for fault diagnosis and classification

inferred← citeshttps://doi.org/10.1007/s40857-021-00222-9openalex-snapshot

Recent Advancement of Deep Learning Applications to Machine Condition Monitoring Part 1: A Critical Review

inferred← citeshttps://doi.org/10.1007/s42417-023-00930-8openalex-snapshot

Bearing Fault Diagnosis in CNC Machine Using Hybrid Signal Decomposition and Gentle AdaBoost Learning

inferred← citeshttps://doi.org/10.1007/s42417-023-00949-xopenalex-snapshot

Fault Diagnosis of Rolling Bearings Based on the Improved Symmetrized Dot Pattern Enhanced Convolutional Neural Networks

inferred← citeshttps://doi.org/10.1007/s42417-024-01405-0openalex-snapshot

Enhanced Bearing Fault Diagnosis Through Trees Ensemble Method and Feature Importance Analysis

inferred← citeshttps://doi.org/10.1007/s42417-025-01966-8openalex-snapshot

Enhanced Fault Diagnosis of Rolling Bearings with Noise Filtering and Neural Networks

inferred← citeshttps://doi.org/10.1007/s42452-020-2741-0openalex-snapshot

Intelligent diagnosis of petroleum equipment faults using a deep hybrid model

inferred← citeshttps://doi.org/10.1016/j.asej.2022.101945openalex-snapshot

A systematic review of rolling bearing fault diagnoses based on deep learning and transfer learning: Taxonomy, overview, application, open challenges, weaknesses and recommendations

inferred← citeshttps://doi.org/10.1016/j.asoc.2019.105958openalex-snapshot

Knowledge distilling based model compression and feature learning in fault diagnosis

inferred← citeshttps://doi.org/10.1016/j.bspc.2022.104000openalex-snapshot

COVID-19 chest X-ray detection through blending ensemble of CNN snapshots

inferred← citeshttps://doi.org/10.1016/j.cie.2025.110988openalex-snapshot

An intelligent data-driven adaptive health state assessment approach for rolling bearings under single and multiple working conditions

inferred← citeshttps://doi.org/10.1016/j.compind.2022.103743openalex-snapshot

A novel information processing method based on an ensemble of Auto-Encoders for unsupervised fault detection

inferred← citeshttps://doi.org/10.1016/j.dsp.2024.104776openalex-snapshot

Bearing faults classification using novel log energy-based empirical mode decomposition and machine Mel-frequency cepstral coefficients

inferred← citeshttps://doi.org/10.1016/j.egyr.2021.11.278openalex-snapshot

Economic indicators and bioenergy supply in developed economies: QROF-DEMATEL and random forest models

inferred← citeshttps://doi.org/10.1016/j.engappai.2022.105633openalex-snapshot

Incipient fault diagnosis of analog circuit with ensemble HKELM based on fused multi-channel and multi-scale features

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.2023.107106openalex-snapshot

Thermographic image-based diagnosis of failures in electrical motors using deep transfer learning

inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107126openalex-snapshot

Review on prognostics and health management in smart factory: From conventional to deep learning perspectives

inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107357openalex-snapshot

A literature review of fault diagnosis based on ensemble learning

inferred← citeshttps://doi.org/10.1016/j.epsr.2024.111392openalex-snapshot

A partial discharge pattern recognition method based on multi-scale adaptive denoising network and Stacking Ensemble Learning

inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122827openalex-snapshot

Graph neural network-based bearing fault diagnosis using Granger causality test

inferred← citeshttps://doi.org/10.1016/j.eswa.2025.126420openalex-snapshot

A robust bearing fault diagnosis method based on ensemble learning with adaptive weight selection

inferred← citeshttps://doi.org/10.1016/j.heliyon.2023.e17584openalex-snapshot

Machine learning for fault analysis in rotating machinery: A comprehensive review

inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e33377openalex-snapshot

Ensemble model for grape leaf disease detection using CNN feature extractors and random forest classifier

inferred← citeshttps://doi.org/10.1016/j.isatra.2022.02.048openalex-snapshot

Industrial gearbox fault diagnosis based on multi-scale convolutional neural networks and thermal imaging

inferred← citeshttps://doi.org/10.1016/j.jfranklin.2025.108219openalex-snapshot

Physics-inspired deep learning network using dilated kronecker convolution for rotary machines under variable operating conditions

inferred← citeshttps://doi.org/10.1016/j.jmsy.2020.12.002openalex-snapshot

A new ensemble convolutional neural network with diversity regularization for fault diagnosis

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.2020.108502openalex-snapshot

A hybrid deep-learning model for fault diagnosis of rolling bearings

inferred← citeshttps://doi.org/10.1016/j.measurement.2020.108603openalex-snapshot

Semi-random subspace with Bi-GRU: Fusing statistical and deep representation features for bearing fault diagnosis

inferred← citeshttps://doi.org/10.1016/j.measurement.2021.109656openalex-snapshot

A study on fault diagnosis of bearing pitting under different speed condition based on an improved inception capsule network

inferred← citeshttps://doi.org/10.1016/j.measurement.2022.111570openalex-snapshot

Cross-Attribute adaptation networks: Distilling transferable features from multiple sampling-frequency source domains for fault diagnosis of wind turbine gearboxes

inferred← citeshttps://doi.org/10.1016/j.measurement.2022.111855openalex-snapshot

Bearing fault diagnosis using time segmented Fourier synchrosqueezed transform images and convolution neural network

inferred← citeshttps://doi.org/10.1016/j.measurement.2023.113711openalex-snapshot

Recent progress and prospective evaluation of fault diagnosis strategies for electrified drive powertrains: A comprehensive review

inferred← citeshttps://doi.org/10.1016/j.measurement.2025.117027openalex-snapshot

A novel approach for bearing fault diagnosis in complex environments using PSO-CWT and SA-FPN

inferred← citeshttps://doi.org/10.1016/j.measurement.2025.118581openalex-snapshot

Assessment of stress identification for high-speed railway axle based on acceleration signals

inferred← citeshttps://doi.org/10.1016/j.neucom.2020.04.073openalex-snapshot

Deep multi-scale convolutional transfer learning network: A novel method for intelligent fault diagnosis of rolling bearings under variable working conditions and domains

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.2021.02.078openalex-snapshot

An optimized adaptive PReLU-DBN for rolling element bearing fault diagnosis

inferred← citeshttps://doi.org/10.1016/j.neucom.2025.129588openalex-snapshot

Data-driven machinery fault diagnosis: A comprehensive review

inferred← citeshttps://doi.org/10.1016/j.ocecoaman.2024.107408openalex-snapshot

Shift of emphasis toward intelligent equipment maintenance in port operations: A critical review of emerging trends and challenges

inferred← citeshttps://doi.org/10.1016/j.psep.2026.108884openalex-snapshot

Deep transfer learning with supervised dynamic sensor scoring for interpretable fault diagnosis in industrial gas turbines

inferred← citeshttps://doi.org/10.1016/j.rineng.2024.102397openalex-snapshot

A review on fault detection and diagnosis of industrial robots and multi-axis machines

inferred← citeshttps://doi.org/10.1016/j.seta.2025.104479openalex-snapshot

Enhancing fuel cell system fault diagnosis: Using a bayesian optimized convolutional neural network-random forest hybrid model

inferred← citeshttps://doi.org/10.1016/j.ymssp.2021.107821openalex-snapshot

Fault diagnosis of rotating machinery components with deep ELM ensemble induced by real-valued output-based diversity metric

inferred← citeshttps://doi.org/10.1016/j.ymssp.2021.108217openalex-snapshot

Robustness enhancement of machine fault diagnostic models for railway applications through data augmentation

inferred← citeshttps://doi.org/10.1016/j.ymssp.2023.110171openalex-snapshot

A physics-informed feature weighting method for bearing fault diagnostics

inferred← citeshttps://doi.org/10.1016/j.ymssp.2025.112467openalex-snapshot

Refined sticking monitoring of drilling tool for drilling rig in underground coal mine: From mechanism analysis to data mining

inferred← citeshttps://doi.org/10.1016/j.ymssp.2026.114762openalex-snapshot

FRP-M2DA: cross-modal multi-source domain adaptation via frequency-domain recurrence and multi-level adversarial alignment for cross-condition bearing fault diagnosis

inferred← citeshttps://doi.org/10.1021/acs.iecr.2c03495openalex-snapshot

Double Branch Rebalanced Network for Class Imbalance Learning in Process Fault Diagnosis

inferred← citeshttps://doi.org/10.1021/acsomega.1c06607openalex-snapshot

Deep Convolutional Neural Network with Deconvolution and a Deep Autoencoder for Fault Detection and Diagnosis

inferred← citeshttps://doi.org/10.1038/s41598-025-85223-8openalex-snapshot

Deep learning based gasket fault detection: a CNN approach

inferred← citeshttps://doi.org/10.1063/5.0131834openalex-snapshot

A fault diagnosis of bearing through SVM classifier and data visualization using PCA

inferred← citeshttps://doi.org/10.1080/08982112.2025.2542281openalex-snapshot

A hybrid machine learning approach for predicting short production stoppages

inferred← citeshttps://doi.org/10.1080/10589759.2024.2441978openalex-snapshot

A light-weight factorized convolutions based dual-input fuzzy-CNN for efficient motor bearing fault diagnosis

inferred← citeshttps://doi.org/10.1080/10589759.2025.2465409openalex-snapshot

Learning sparse convolutional neural networks through filter pruning for efficient fault diagnosis on edge devices

inferred← citeshttps://doi.org/10.1080/10589759.2025.2548338openalex-snapshot

Modified Grammian Angular Field for spatially informed induction motor fault diagnosis using feature fusion for fault tolerant control applications

inferred← citeshttps://doi.org/10.1080/17538947.2025.2497488openalex-snapshot

Synergistic hyperspectral and SAR imagery retrieval of mangrove leaf area index using adaptive ensemble learning and deep learning algorithms

inferred← citeshttps://doi.org/10.1080/23080477.2024.2364537openalex-snapshot

Exploring evolutionary-tuned autoencoder-based architectures for fault diagnosis in a wind turbine gearbox

inferred← citeshttps://doi.org/10.1088/1361-6501/ab89e3openalex-snapshot

A deep condition feature learning approach for rotating machinery based on MMSDE and optimized SAEs

inferred← citeshttps://doi.org/10.1088/1361-6501/ab8feeopenalex-snapshot

Network-combined broad learning and transfer learning: a new intelligent fault diagnosis method for rolling bearings

inferred← citeshttps://doi.org/10.1088/1361-6501/ac3a31openalex-snapshot

An unsupervised bearing fault diagnosis based on deep subdomain adaptation under noise and variable load condition

inferred← citeshttps://doi.org/10.1088/1361-6501/acb9aaopenalex-snapshot

Adaptive weight-based capsule neural network for bearing fault diagnosis

inferred← citeshttps://doi.org/10.1088/1361-6501/acf1baopenalex-snapshot

Domain adaptive networks with limited data for rotating machinery fault diagnosis: a case of study of gears

inferred← citeshttps://doi.org/10.1088/1361-6501/ad2a31openalex-snapshot

A lifetime prediction model based on two-path convolution with attention mechanism and bidirectional long short-term memory network

inferred← citeshttps://doi.org/10.1088/1361-6501/ad4d16openalex-snapshot

A noise-robust CNN architecture with global attention and gated convolutional Kernels for bearing fault detection

inferred← citeshttps://doi.org/10.1088/1402-4896/ad562aopenalex-snapshot

A machine learning ensemble approach for predicting solar-sensitive hybrid photocatalysts on hydrogen evolution

inferred← citeshttps://doi.org/10.1088/2631-8695/ad5d51openalex-snapshot

A comparative study of heterogeneous machine learning algorithms for arrhythmia classification using feature selection technique and multi-dimensional datasets

inferred← citeshttps://doi.org/10.1088/2631-8695/adf8bcopenalex-snapshot

Improved swin transformer integrated with GADF method for bearing fault detection

inferred← citeshttps://doi.org/10.1088/2631-8695/ae1717openalex-snapshot

A novel CNN-based selective ensemble learning method for gearbox fault diagnosis

inferred← citeshttps://doi.org/10.1088/2631-8695/ae79dbopenalex-snapshot

Few-shot bearing fault diagnosis: a transfer learning framework via time–frequency information fusion

inferred← citeshttps://doi.org/10.1088/2631-8695/aea803openalex-snapshot

Elevator fault diagnosis incorporating multi-scale prototype diffusion enhancement

inferred← citeshttps://doi.org/10.1109/access.2019.2938227openalex-snapshot

Challenges and Opportunities of Deep Learning Models for Machinery Fault Detection and Diagnosis: A Review

inferred← citeshttps://doi.org/10.1109/access.2019.2950985openalex-snapshot

A Review on Deep Learning Applications in Prognostics and Health Management

inferred← citeshttps://doi.org/10.1109/access.2019.2953490openalex-snapshot

Fault Diagnosis of Rotating Machinery Based on Combination of Deep Belief Network and One-dimensional Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/access.2020.2990528openalex-snapshot

Bearing Fault Detection and Diagnosis Using Case Western Reserve University Dataset With Deep Learning Approaches: A Review

inferred← citeshttps://doi.org/10.1109/access.2020.2992231openalex-snapshot

A New Convolutional Neural Network With Random Forest Method for Hydrogen Sensor Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/access.2020.3016888openalex-snapshot

Rolling Bearing Fault Diagnosis Using Time-Frequency Analysis and Deep Transfer Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/access.2021.3063929openalex-snapshot

An Efficient Rolling Bearing Fault Diagnosis Method Based on Spark and Improved Random Forest Algorithm

inferred← citeshttps://doi.org/10.1109/access.2021.3130905openalex-snapshot

Ensemble Pruning of RF via Multi-Objective TLBO Algorithm and Its Parallelization on Spark

inferred← citeshttps://doi.org/10.1109/access.2022.3157820openalex-snapshot

Feature Engineering and Artificial Intelligence-Supported Approaches Used for Electric Powertrain Fault Diagnosis: A Review

inferred← citeshttps://doi.org/10.1109/access.2022.3167761openalex-snapshot

Fault Diagnosis of Bearings With the Common-Domain Data

inferred← citeshttps://doi.org/10.1109/access.2022.3177650openalex-snapshot

Fault Diagnosis Method of Rolling Bearing Based on Variational Modal Decomposition Multisynchrosqueezing Transform Combined With Long Short-Term Memory Networks

inferred← citeshttps://doi.org/10.1109/access.2023.3299852openalex-snapshot

Fault Diagnosis of Cascaded Multilevel Inverter Using Multiscale Kernel Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/access.2024.3366810openalex-snapshot

Machine Learning for Inverter-Fed Motors Monitoring and Fault Detection: An Overview

inferred← citeshttps://doi.org/10.1109/access.2024.3431040openalex-snapshot

Novel Machine Learning Techniques for Classification of Rolling Bearings

inferred← citeshttps://doi.org/10.1109/access.2024.3447077openalex-snapshot

Motor Operational Settings Prediction for Sustainable Manufacturing Facilities

inferred← citeshttps://doi.org/10.1109/access.2025.3548693openalex-snapshot

Research on Bearing Fault Diagnosis Methods Based on Various Convolutional Neural Network Architectures

inferred← citeshttps://doi.org/10.1109/access.2025.3577672openalex-snapshot

Bearing Fault Diagnosis in Induction Motors Using Low-Cost Triaxial ADXL355 Accelerometer and a Hybrid CWT-DCNN-LSTM Model

inferred← citeshttps://doi.org/10.1109/aieee51419.2021.9435792openalex-snapshot

Investigation of Deep Neural Networks for Hypoid Gear Signal Classification to Identify Anomalies

inferred← citeshttps://doi.org/10.1109/bec56180.2022.9935614openalex-snapshot

The Impact of Load on Global Parameters of Electrical Machines in Case of Healthy and Broken Rotor Bars

inferred← citeshttps://doi.org/10.1109/cac53003.2021.9728363openalex-snapshot

A rolling bearing fault diagnosis model based on WCNN-BiGRU

inferred← citeshttps://doi.org/10.1109/ccdc69976.2026.11560732openalex-snapshot

An Integrated Transfer-Learning Framework for Intelligent Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/citsm64103.2024.10775699openalex-snapshot

Deepfake Video Classification Using Random Forest and Stochastic Gradient Descent with Triplet Loss Approach Algorithm

inferred← citeshttps://doi.org/10.1109/coase.2019.8843068openalex-snapshot

Data-Driven Fault Diagnostics and Prognostics for Predictive Maintenance: A Brief Overview

inferred← citeshttps://doi.org/10.1109/cyber50695.2020.9279185openalex-snapshot

Research on Intelligent Fault Diagnosis Method for Rolling Bearing Based on One-Dimensional LeNet-5 Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/eit57321.2023.10187360openalex-snapshot

An investigation of the Intrusion detection system for the NSL-KDD dataset using machine-learning algorithms

inferred← citeshttps://doi.org/10.1109/ficloud49777.2021.00048openalex-snapshot

A Comparison of Deep Transfer Learning Methods on Bearing Fault Detection

inferred← citeshttps://doi.org/10.1109/icaiis49377.2020.9194866openalex-snapshot

Machine Fault Diagnosis Based on Wavelet Packet Coefficients and 1D Convolutional Neural Networks

inferred← citeshttps://doi.org/10.1109/iccci59363.2023.10210100openalex-snapshot

A Heterogeneous Ensemble Learning Approach for Leather Species Prediction

inferred← citeshttps://doi.org/10.1109/iceccme64568.2025.11277916openalex-snapshot

Sensor Fusion and Fault Diagnosis in Mechatronic Systems using Temporal Convolutional Networks

inferred← citeshttps://doi.org/10.1109/icercs57948.2023.10434234openalex-snapshot

Fault Diagnosis Using a Resnet-based Deep Learning Multilayer Fault Detection Model

inferred← citeshttps://doi.org/10.1109/icphm53196.2022.9815755openalex-snapshot

An Integration of Spectrum Analysis and Attention-based Network for Condition Monitoring of Vibration Components

inferred← citeshttps://doi.org/10.1109/icrms59672.2023.00057openalex-snapshot

Case Study of Bearing Fault Diagnosis Based on Vibration Signal and Fault Injection

inferred← citeshttps://doi.org/10.1109/icsmd57530.2022.10058221openalex-snapshot

Fault Diagnosis Method of Rolling Bearings Under Different Working Conditions Based on Federated Feature Transfer Learning

inferred← citeshttps://doi.org/10.1109/icspis54653.2021.9729385openalex-snapshot

Intelligent Fault Diagnosis of Rolling BearingBased on Deep Transfer Learning Using Time-Frequency Representation

inferred← citeshttps://doi.org/10.1109/icsrs59833.2023.10381093openalex-snapshot

An Intelligent Dynamic Fault Diagnostic Model for Rotating Machinery

inferred← citeshttps://doi.org/10.1109/indin58382.2024.10774451openalex-snapshot

Research on Bearing Fault Diagnosis Based on DT-RF-NB Ensemble Model

inferred← citeshttps://doi.org/10.1109/iscid51228.2020.00091openalex-snapshot

Fault Diagnosis for Rotating Machinery Gearbox based on 1DCNN-RF

inferred← citeshttps://doi.org/10.1109/isie62713.2025.11124639openalex-snapshot

Cyberphysical Fault Propagation and Detection in Connected Electric Vehicles

inferred← citeshttps://doi.org/10.1109/ithings-greencom-cpscom-smartdata-cybermatics55523.2022.00091openalex-snapshot

Research on rolling bearing fault diagnosis method based on hybrid deep learning network model

inferred← citeshttps://doi.org/10.1109/itsc45102.2020.9294269openalex-snapshot

Empirical Study on Robustness of Machine Learning Approaches for Fault Diagnosis under Railway Operational Conditions

inferred← citeshttps://doi.org/10.1109/jestpe.2022.3228421openalex-snapshot

Series Arc Fault Identification in DC Distribution Based on Random Forest Predicted Probability

inferred← citeshttps://doi.org/10.1109/jsen.2023.3265409openalex-snapshot

A Fault Diagnosis Method of Rolling Bearing Based on Improved Recurrence Plot and Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/jsen.2023.3285531openalex-snapshot

Artificial Intelligence Technique-Based EV Powertrain Condition Monitoring and Fault Diagnosis: A Review

inferred← citeshttps://doi.org/10.1109/jsen.2024.3409768openalex-snapshot

A Novel Small-Sample Fault Diagnosis Method for Rolling Bearings via Continuous Wavelet Transform and Siamese Neural Network

inferred← citeshttps://doi.org/10.1109/jstars.2019.2953234openalex-snapshot

Very High Resolution Remote Sensing Imagery Classification Using a Fusion of Random Forest and Deep Learning Technique—Subtropical Area for Example

inferred← citeshttps://doi.org/10.1109/jstars.2021.3109661openalex-snapshot

A Multiscale Attention Network for Remote Sensing Scene Images Classification

inferred← citeshttps://doi.org/10.1109/phm-besancon49106.2020.00024openalex-snapshot

Data-Driven Prognostics of Alternating Current Solenoid Valves

inferred← citeshttps://doi.org/10.1109/phm-nanjing52125.2021.9613092openalex-snapshot

NSP-CNN Rolling Bearing Fault Diagnosis Method

inferred← citeshttps://doi.org/10.1109/phm-xian66756.2025.11427684openalex-snapshot

A high-precision spacecraft bearing fault diagnosis method based on improved EMD-CNN-LSTM fusion

inferred← citeshttps://doi.org/10.1109/phm-yantai55411.2022.9941774openalex-snapshot

Unsupervised Fault Detection of Industrial Robot Joints Using Current Signal

inferred← citeshttps://doi.org/10.1109/phm58589.2023.00063openalex-snapshot

Bearing Fault Diagnosis Based on Diffusion Model and One-Class Support Vector Machine

inferred← citeshttps://doi.org/10.1109/rcae59706.2023.10398828openalex-snapshot

A Rolling Bearing Fault Diagnosis Method Based on Generalized Dataset Realizing Small Sample Transfer Learning

inferred← citeshttps://doi.org/10.1109/sceecs61402.2024.10482034openalex-snapshot

A Critical Insight and Evaluation of AI Models for Predictive Maintenance under Industry 4.0

inferred← citeshttps://doi.org/10.1109/smartcomp65954.2025.00109openalex-snapshot

Video-on-Demand Prediction via Ensemble Load-Adjusted CNN-Random Forests

inferred← citeshttps://doi.org/10.1109/tii.2020.2973731openalex-snapshot

Industrial Data-Driven Monitoring Based on Incremental Learning Applied to the Detection of Novel Faults

inferred← citeshttps://doi.org/10.1109/tii.2022.3177662openalex-snapshot

A Hierarchical Training-Convolutional Neural Network for Imbalanced Fault Diagnosis in Complex Equipment

inferred← citeshttps://doi.org/10.1109/tii.2022.3183225openalex-snapshot

A Compressed Unsupervised Deep Domain Adaptation Model for Efficient Cross-Domain Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tii.2022.3205373openalex-snapshot

Few-Shot Learning for Fault Diagnosis With a Dual Graph Neural Network

inferred← citeshttps://doi.org/10.1109/tim.2021.3122184openalex-snapshot

Intelligent Bearing Fault Diagnosis Based on Scaled Ramanujan Filter Banks in Noisy Environments

inferred← citeshttps://doi.org/10.1109/tim.2021.3132989openalex-snapshot

An Early Fault Detection Method of Rotating Machines Based on Unsupervised Sequence Segmentation Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/tim.2022.3225910openalex-snapshot

A Novel Ensemble Learning-Based Multisensor Information Fusion Method for Rolling Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2023.3259031openalex-snapshot

Attention-Embedded Quadratic Network (Qttention) for Effective and Interpretable Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2024.3351229openalex-snapshot

A Low-Power Hierarchical CNN Hardware Accelerator for Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2026.3701209openalex-snapshot

LMQBDANet: A Lightweight Rolling Bearing Fault Diagnosis Model With Multiscale Quadratic and Broadcast Denoising Attention

inferred← citeshttps://doi.org/10.1142/s0219749923500272openalex-snapshot

An efficient combination strategy for hybrid quantum ensemble classifier

inferred← citeshttps://doi.org/10.1145/3442536.3442542openalex-snapshot

CNN as a feature extractor in gaze recognition

inferred← citeshttps://doi.org/10.1145/3640115.3640164openalex-snapshot

Convolutional Neural Network-Based Research on Software Engineering Defect Prediction

inferred← citeshttps://doi.org/10.1155/2019/3262818openalex-snapshot

A Fault Diagnosis Method for One‐Dimensional Vibration Signal Based on Multiresolution tlsDMD and Approximate Entropy

inferred← citeshttps://doi.org/10.1155/2021/2149048openalex-snapshot

Compound Fault Diagnosis of Stator Interturn Short Circuit and Air Gap Eccentricity Based on Random Forest and XGBoost

inferred← citeshttps://doi.org/10.1155/2021/6053824openalex-snapshot

An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network

inferred← citeshttps://doi.org/10.1155/2021/6221545openalex-snapshot

Bearing Faulty Prognostic Approach Based on Multiscale Feature Extraction and Attention Learning Mechanism

inferred← citeshttps://doi.org/10.1155/2021/6653595openalex-snapshot

Application of Vibration Signals for the Quantitative Analysis of the Optimal Threshold of Bearing Failure

inferred← citeshttps://doi.org/10.1155/2021/7331692openalex-snapshot

Research on the Improved CNN Deep Learning Method for Motion Intention Recognition of Dynamic Lower Limb Prosthesis

showing the first 200 of 312 · page through all 312

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.