On the public citation graph

Multiscale Convolutional Neural Network With Feature Alignment for Bearing Fault Diagnosis

https://doi.org/10.1109/tim.2021.3077673

0 signed · 138 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1002/stc.2651openalex-snapshot

Deep‐learning‐based guided wave detection for liquid‐level state in porcelain bushing type terminal

inferredcites →https://doi.org/10.1007/s10845-020-01600-2openalex-snapshot

Bearing fault diagnosis base on multi-scale CNN and LSTM model

inferredcites →https://doi.org/10.1016/j.compind.2018.12.013openalex-snapshot

A novel convolutional neural network based fault recognition method via image fusion of multi-vibration-signals

inferredcites →https://doi.org/10.1016/j.eng.2017.05.015openalex-snapshot

Intelligent Manufacturing in the Context of Industry 4.0: A Review

inferredcites →https://doi.org/10.1016/j.knosys.2019.105022openalex-snapshot

Enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy for early fault prognosis of bearing

inferredcites →https://doi.org/10.1016/j.knosys.2020.106396openalex-snapshot

Ensemble transfer CNNs driven by multi-channel signals for fault diagnosis of rotating machinery cross working conditions

inferredcites →https://doi.org/10.1016/j.measurement.2019.107393openalex-snapshot

Transfer fault diagnosis of bearing installed in different machines using enhanced deep auto-encoder

inferredcites →https://doi.org/10.1016/j.neucom.2019.05.052openalex-snapshot

An improved deep convolutional neural network with multi-scale information for bearing fault diagnosis

inferredcites →https://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

inferredcites →https://doi.org/10.1016/j.renene.2020.02.004openalex-snapshot

Intelligent fault diagnosis of Wind Turbines via a Deep Learning Network Using Parallel Convolution Layers with Multi-Scale Kernels

inferredcites →https://doi.org/10.1016/j.sigpro.2013.04.015openalex-snapshot

Wavelets for fault diagnosis of rotary machines: A review with applications

inferredcites →https://doi.org/10.1016/j.ymssp.2018.03.025openalex-snapshot

Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization

inferredcites →https://doi.org/10.1016/j.ymssp.2018.05.050openalex-snapshot

Deep learning and its applications to machine health monitoring

inferredcites →https://doi.org/10.1016/j.ymssp.2019.106272openalex-snapshot

Mechanical fault diagnosis using Convolutional Neural Networks and Extreme Learning Machine

inferredcites →https://doi.org/10.1016/j.ymssp.2019.106609openalex-snapshot

A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests

inferredcites →https://doi.org/10.1016/j.ymssp.2020.106683openalex-snapshot

A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks

inferredcites →https://doi.org/10.1088/1361-6501/abaf2bopenalex-snapshot

Model-based detection of soft faults using the smoothed residual for a control system

inferredcites →https://doi.org/10.1109/access.2018.2886343openalex-snapshot

Deep Decoupling Convolutional Neural Network for Intelligent Compound Fault Diagnosis

inferredcites →https://doi.org/10.1109/icsmd50554.2020.9261675openalex-snapshot

Deep Feature-aligned Convolutional Neural Network for Machinery Fault Diagnosis

inferredcites →https://doi.org/10.1109/jsen.2020.3009194openalex-snapshot

Multi-Task Deep Transfer Learning Method for Guided Wave-Based Integrated Health Monitoring Using Piezoelectric Transducers

inferredcites →https://doi.org/10.1109/tfuzz.2019.2914617openalex-snapshot

Deep Fuzzy Echo State Networks for Machinery Fault Diagnosis

inferredcites →https://doi.org/10.1109/tii.2018.2793246openalex-snapshot

Deep Coupling Autoencoder for Fault Diagnosis With Multimodal Sensory Data

inferredcites →https://doi.org/10.1109/tii.2019.2917233openalex-snapshot

Intelligent Fault Diagnosis for Rotary Machinery Using Transferable Convolutional Neural Network

inferredcites →https://doi.org/10.1109/tii.2020.2964117openalex-snapshot

A Robust Weight-Shared Capsule Network for Intelligent Machinery Fault Diagnosis

inferredcites →https://doi.org/10.1109/tim.2017.2669947openalex-snapshot

Multisensor Feature Fusion for Bearing Fault Diagnosis Using Sparse Autoencoder and Deep Belief Network

inferredcites →https://doi.org/10.1109/tim.2019.2924509openalex-snapshot

Research on Remaining Useful Life Prediction of Rolling Element Bearings Based on Time-Varying Kalman Filter

inferredcites →https://doi.org/10.1109/tim.2019.2925247openalex-snapshot

DCNN-Based Multi-Signal Induction Motor Fault Diagnosis

inferredcites →https://doi.org/10.1109/tim.2019.2956332openalex-snapshot

A New Intelligent Bearing Fault Diagnosis Method Using SDP Representation and SE-CNN

inferredcites →https://doi.org/10.1109/tim.2019.2958010openalex-snapshot

Deep Ensemble Capsule Network for Intelligent Compound Fault Diagnosis Using Multisensory Data

inferredcites →https://doi.org/10.1109/tim.2020.2992829openalex-snapshot

Deep Semi-supervised Domain Generalization Network for Rotary Machinery Fault Diagnosis under Variable Speed

inferredcites →https://doi.org/10.1109/tim.2020.3042300openalex-snapshot

Deep Adversarial Capsule Network for Compound Fault Diagnosis of Machinery Toward Multidomain Generalization Task

inferredcites →https://doi.org/10.1109/tmech.2020.3025615openalex-snapshot

A Two-Stage Transfer Adversarial Network for Intelligent Fault Diagnosis of Rotating Machinery With Multiple New Faults

inferredcites →https://doi.org/10.1186/s40537-019-0197-0openalex-snapshot

A survey on Image Data Augmentation for Deep Learning

inferredcites →https://doi.org/10.3390/s17020425openalex-snapshot

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

inferredcites →https://doi.org/10.3724/sp.j.1187.2010.00001openalex-snapshot

A review: Prognostics and health management

inferredcites →https://doi.org/10.48550/arxiv.1805.12177openalex-snapshot

Why do deep convolutional networks generalize so poorly to small image transformations?

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.4517121openalex-extracted

inferred← citeshttps://doi.org/10.1007/978-981-99-6187-0_6openalex-snapshot

An Anti-interference Mechanical Fault Diagnosis Method Based on CNN and Attention Mechanism

inferred← citeshttps://doi.org/10.1007/s11227-025-07597-wopenalex-snapshot

An attentional fusion-based method for coal-gangue recognition in noisy environment of generalised workface

inferred← citeshttps://doi.org/10.1007/s11760-025-03848-8openalex-snapshot

A robust deep learning system for motor bearing fault detection: leveraging multiple learning strategies and a novel double loss function

inferred← citeshttps://doi.org/10.1007/s12206-026-0303-0openalex-snapshot

Few-shot transfer learning on multiple deep networks for bearing fault diagnosis under variable working conditions

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/s40430-023-04426-0openalex-snapshot

Fault diagnosis based on feature enhancement and spatial adjacent region dropout strategy

inferred← citeshttps://doi.org/10.1016/j.aei.2023.101883openalex-snapshot

Deep continual transfer learning with dynamic weight aggregation for fault diagnosis of industrial streaming data under varying working conditions

inferred← citeshttps://doi.org/10.1016/j.apacoust.2023.109436openalex-snapshot

The LST-SATM-net: A new deep feature learning framework for aero-engine hydraulic pipeline systems intelligent faults diagnosis

inferred← citeshttps://doi.org/10.1016/j.compeleceng.2025.110633openalex-snapshot

A novel intra-layer mixed bit-width quantization method for the classification of 1D periodic time-series signals

inferred← citeshttps://doi.org/10.1016/j.compind.2022.103810openalex-snapshot

In-situ fault detection for the spindle motor of CNC machines via multi-stage residual fusion convolution neural networks

inferred← citeshttps://doi.org/10.1016/j.dsp.2025.105682openalex-snapshot

DWTNet: A novel dual-branch interactive network for fault feature extraction of rotating machinery

inferred← citeshttps://doi.org/10.1016/j.engfailanal.2025.109474openalex-snapshot

A limited annotated sample fault diagnosis algorithm based on nonlinear coupling self-attention mechanism

inferred← citeshttps://doi.org/10.1016/j.eswa.2023.120957openalex-snapshot

MSRCN: A cross-machine diagnosis method for the CNC spindle motors with compound faults

inferred← citeshttps://doi.org/10.1016/j.jmsy.2022.12.001openalex-snapshot

In-situ fault diagnosis for the harmonic reducer of industrial robots via multi-scale mixed convolutional neural networks

inferred← citeshttps://doi.org/10.1016/j.knosys.2022.109846openalex-snapshot

Transfer learning based on improved stacked autoencoder for bearing fault diagnosis

inferred← citeshttps://doi.org/10.1016/j.knosys.2023.111158openalex-snapshot

Fault diagnosis in rotating machines based on transfer learning: Literature review

inferred← citeshttps://doi.org/10.1016/j.knosys.2024.112361openalex-snapshot

AMCW-DFFNSA: An interpretable deep feature fusion network for noise-robust machinery fault diagnosis

inferred← citeshttps://doi.org/10.1016/j.rcim.2023.102684openalex-snapshot

Manipulator joint fault localization for intelligent flexible manufacturing based on reinforcement learning and robot dynamics

inferred← citeshttps://doi.org/10.1016/j.ymssp.2021.108487openalex-snapshot

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges

inferred← citeshttps://doi.org/10.1016/j.ymssp.2022.109569openalex-snapshot

Discriminative feature learning using a multiscale convolutional capsule network from attitude data for fault diagnosis of industrial robots

inferred← citeshttps://doi.org/10.1016/j.ymssp.2022.109615openalex-snapshot

A novel unsupervised directed hierarchical graph network with clustering representation for intelligent fault diagnosis of machines

inferred← citeshttps://doi.org/10.1016/j.ymssp.2024.111142openalex-snapshot

Dconformer: A denoising convolutional transformer with joint learning strategy for intelligent diagnosis of bearing faults

inferred← citeshttps://doi.org/10.1038/s41598-022-22171-7openalex-snapshot

Deep residual neural-network-based robot joint fault diagnosis method

inferred← citeshttps://doi.org/10.1038/s41598-024-66541-9openalex-snapshot

Hydraulic system fault diagnosis decoupling method based on 2D time-series modeling and self-attention fusion

inferred← citeshttps://doi.org/10.1049/cim2.12055openalex-snapshot

Intelligent fault diagnosis of rotating machinery using lightweight network with modified tree‐structured parzen estimators

inferred← citeshttps://doi.org/10.1049/elp2.70173openalex-snapshot

A Robust Multi‐Domain Signal Processing Framework for Early Detection of Ball Bearing Faults in Noisy and Variable Load Conditions

inferred← citeshttps://doi.org/10.1049/smt2.12213openalex-snapshot

Universal domain adaptation for machinery fault diagnosis based on multi‐scale dual attention network and entropy‐based clustering

inferred← citeshttps://doi.org/10.1063/5.0333221openalex-snapshot

A slow-feature-enhanced dual-stream deep network for Czochralski crystal growth condition monitoring in semiconductor silicon single crystal manufacturing process

inferred← citeshttps://doi.org/10.1088/1361-6501/ac3942openalex-snapshot

Transfer learning method for rolling bearing fault diagnosis under different working conditions based on CycleGAN

inferred← citeshttps://doi.org/10.1088/1361-6501/ad2828openalex-snapshot

Adversarial training of multi-scale channel attention network for enhanced robustness in bearing fault diagnosis

inferred← citeshttps://doi.org/10.1088/1361-6501/ad78f1openalex-snapshot

MRNet: rolling bearing fault diagnosis in noisy environment based on multi-scale residual convolutional network

inferred← citeshttps://doi.org/10.1088/1361-6501/adb061openalex-snapshot

A novel frequency attention mechanism for FEM-assisted bearing fault diagnosis

inferred← citeshttps://doi.org/10.1088/1361-6501/add0ceopenalex-snapshot

Rolling bearings fault diagnosis using a one-dimensional vision transformer with multi-scale residual convolution

inferred← citeshttps://doi.org/10.1088/1361-6501/add316openalex-snapshot

A rolling bearing fault diagnosis method based on feature fusion threshold attention residual network and enhanced transformer under small samples and strong noise

inferred← citeshttps://doi.org/10.1088/1361-6501/ae7998openalex-snapshot

A prior-guided dynamic fusion framework for dual-branch multi-domain fault diagnosis of rotating machinery

inferred← citeshttps://doi.org/10.1088/2631-8695/adaca6openalex-snapshot

Rolling bearing fault diagnosis based on iDBO-VMD-LSSVM

inferred← citeshttps://doi.org/10.1088/2631-8695/ae29bdopenalex-snapshot

EPA-RepViT: a lightweight model for fault diagnosis of planetary gearbox under strong noise

inferred← citeshttps://doi.org/10.1093/jcde/qwad076openalex-snapshot

Multi-head de-noising autoencoder-based multi-task model for fault diagnosis of rolling element bearings under various speed conditions

inferred← citeshttps://doi.org/10.1109/access.2023.3257101openalex-snapshot

Identifying Bearing Faults Using Multiscale Residual Attention and Multichannel Neural Network

inferred← citeshttps://doi.org/10.1109/access.2024.3522948openalex-snapshot

Enhanced Fault Diagnosis in Rotating Machinery Using a Hybrid CWT-LeNet-5-LSTM Model: Performance Across Various Load Conditions

inferred← citeshttps://doi.org/10.1109/access.2026.3651187openalex-snapshot

Explainable AI-Driven Intrusion Detection System for DoS Attack Classification Using Deep Learning and Optimization Techniques

inferred← citeshttps://doi.org/10.1109/aiita69518.2026.11567268openalex-snapshot

EWSNet: Enhanced Semi-Shrinkage Wavelet Weight Initialization Network for Robust Rolling Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/ainit61980.2024.10581767openalex-snapshot

Fault Diagnosis of Bearings Using MSCPCNN with Limited Samples

inferred← citeshttps://doi.org/10.1109/ddcls61622.2024.10606633openalex-snapshot

SFS-PSO: An Improved Data Preprocessing Approach in Fault Diagnosis under Variable Working Conditions

inferred← citeshttps://doi.org/10.1109/icftic68075.2025.11324884openalex-snapshot

A Data Generation Method for Small-Sample Fault Diagnosis of Meteorological Equipment

inferred← citeshttps://doi.org/10.1109/icsmd53520.2021.9670854openalex-snapshot

Federated Learning for Bearing Fault Diagnosis with Dynamic Weighted Averaging

inferred← citeshttps://doi.org/10.1109/jsen.2023.3265675openalex-snapshot

Coupled Hybrid Stochastic Resonance With Multiobjective Optimization for Machinery Dynamic Signature and Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/jsen.2023.3348597openalex-snapshot

Rotary Machinery Fault Diagnosis Based on Split Attention Mechanism and Graph Convolutional Domain Adaptive Adversarial Network

inferred← citeshttps://doi.org/10.1109/jsen.2024.3432921openalex-snapshot

Improved Depthwise Separable Convolution for Transfer Learning in Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/jsen.2026.3657750openalex-snapshot

A Novel Spatial-Temporal Graph Neural Network for Major Depressive Disorder Detection Based on Resting State EEG Signals

inferred← citeshttps://doi.org/10.1109/ojim.2022.3190535openalex-snapshot

Effective Convolutional Transformer for Highly Accurate Planetary Gearbox Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/phm-xian66756.2025.11427783openalex-snapshot

BSLM-CDAN: Batch-Norm-Stabilized and Locality-Weighted Conditional Adaptation for Cross-Condition Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tase.2025.3579694openalex-snapshot

Noise Adaptive Filtering Neural Network Under Multiscale Features

inferred← citeshttps://doi.org/10.1109/tcyb.2022.3195355openalex-snapshot

A Multi-Source Weighted Deep Transfer Network for Open-Set Fault Diagnosis of Rotary Machinery

inferred← citeshttps://doi.org/10.1109/tii.2024.3384603openalex-snapshot

Cross-Domain Compound Fault Diagnosis of Machine-Level Motors via Time–Frequency Self-Contrastive Learning

inferred← citeshttps://doi.org/10.1109/tim.2022.3180417openalex-snapshot

Federated Transfer Learning for Bearing Fault Diagnosis With Discrepancy-Based Weighted Federated Averaging

inferred← citeshttps://doi.org/10.1109/tim.2022.3184368openalex-snapshot

Similarity Metric-Based Metalearning Network Combining Prior Metatraining Strategy for Intelligent Fault Detection Under Small Samples Prerequisite

inferred← citeshttps://doi.org/10.1109/tim.2022.3190525openalex-snapshot

Full Attention Wasserstein GAN With Gradient Normalization for Fault Diagnosis Under Imbalanced Data

inferred← citeshttps://doi.org/10.1109/tim.2022.3196742openalex-snapshot

Multiscale Residual Attention Convolutional Neural Network for Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2022.3211559openalex-snapshot

A Novel Complex Network-Based Graph Convolutional Network in Major Depressive Disorder Detection

inferred← citeshttps://doi.org/10.1109/tim.2022.3227609openalex-snapshot

Residual-Hypergraph Convolution Network: A Model-Based and Data-Driven Integrated Approach for Fault Diagnosis in Complex Equipment

inferred← citeshttps://doi.org/10.1109/tim.2022.3231325openalex-snapshot

Lightweight Multiscale Convolutional Networks With Adaptive Pruning for Intelligent Fault Diagnosis of Train Bogie Bearings in Edge Computing Scenarios

inferred← citeshttps://doi.org/10.1109/tim.2023.3259032openalex-snapshot

Fault Diagnosis of Bearings and Gears Based on LiteNet With Feature Aggregation

inferred← citeshttps://doi.org/10.1109/tim.2023.3280503openalex-snapshot

Zero-Shot Compound Fault Diagnosis Method Based on Semantic Learning and Discriminative Features

inferred← citeshttps://doi.org/10.1109/tim.2023.3298653openalex-snapshot

A Novel Local Binary Temporal Convolutional Neural Network for Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2023.3322485openalex-snapshot

Cross-Conditions Fault Diagnosis of Rolling Bearings Based on Dual Domain Adversarial Network

inferred← citeshttps://doi.org/10.1109/tim.2023.3343775openalex-snapshot

An Investigation Into the Behavior of Intelligent Fault Diagnostic Models Under Imbalanced Data

inferred← citeshttps://doi.org/10.1109/tim.2023.3345910openalex-snapshot

FedAlign: Federated Model Alignment via Data-Free Knowledge Distillation for Machine Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2023.3348910openalex-snapshot

SWDAE: A New Degradation State Evaluation Method for Metro Wheels With Interpretable Health Indicator Construction Based on Unsupervised Deep Learning

inferred← citeshttps://doi.org/10.1109/tim.2024.3374311openalex-snapshot

Deep Learning-Based Bearing Fault Diagnosis Using a Trusted Multiscale Quadratic Attention-Embedded Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/tim.2024.3453312openalex-snapshot

Cascading Time-Frequency Transformer and Spatio-Temporal Graph Attention Network for Rotating Machinery Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2024.3470961openalex-snapshot

Zero-Shot Compound Fault Diagnosis Method Using Semantic Construction and Embedding

inferred← citeshttps://doi.org/10.1109/tim.2024.3509579openalex-snapshot

SMLFormer: A Lightweight and Robust Framework for Intelligent In-Transit Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2025.3542867openalex-snapshot

Multiscale Dynamic Weight-Based Mixed Convolutional Neural Network for Fault Diagnosis of Rotating Machinery

inferred← citeshttps://doi.org/10.1109/tim.2025.3544700openalex-snapshot

Learning Interpretable and Transferable Representations via Wavelet-Constrained Transformer for Industrial Acoustic Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2025.3545974openalex-snapshot

Optimal Transport Deep Clustering Network for Universal-Set Transfer Bearing Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tim.2025.3552473openalex-snapshot

Extended Sliding Time Synchronous Averaging for Enhancing Weak Fault Feature of Rolling Bearings

inferred← citeshttps://doi.org/10.1109/tim.2025.3614827openalex-snapshot

A Multiscale Recalibration Attention Network With Adaptive Grouped Convolution for Bearing Fault Diagnosis via Transfer Learning

inferred← citeshttps://doi.org/10.1109/tim.2025.3632429openalex-snapshot

Dynamic Sparse Multiscale Convolutional Network: A New Lightweight Framework With Joint Pruning Optimization for Edge Fault Diagnosis of Train Transmission Systems

inferred← citeshttps://doi.org/10.1109/tmech.2022.3214865openalex-snapshot

Fast Robust Capsule Network With Dynamic Pruning and Multiscale Mutual Information Maximization for Compound-Fault Diagnosis

inferred← citeshttps://doi.org/10.1109/tmech.2025.3649879openalex-snapshot

From Vibration to Motor Current: A Cross-Modal Meta-Learning-Driven Fault Diagnosis Framework for Harmonic Drive of Industrial Robots

inferred← citeshttps://doi.org/10.1109/tr.2025.3648784openalex-snapshot

A Novel Multidynamic Domain Adaptation Transfer Learning Method for Fault Diagnosis of Bearings With Insufficient Labeled Data

inferred← citeshttps://doi.org/10.1177/14759217251352082openalex-snapshot

Deep capsule networks based on dual heterogeneous feature resonance fusion for mechanical fault diagnosis

inferred← citeshttps://doi.org/10.12677/dsc.2026.153026openalex-snapshot

Design of a High-Resolution Capacitive Tactile Sensor Micro-Capacitor Detection System

inferred← citeshttps://doi.org/10.1371/journal.pone.0314898openalex-snapshot

Rolling bearing fault diagnosis method based on gramian angular difference field and dynamic self-calibrated convolution module

inferred← citeshttps://doi.org/10.17531/ein/192167openalex-snapshot

Rolling bearing fault diagnosis method based on multi-scale pooling residual convolutional neural network under noisy environment

inferred← citeshttps://doi.org/10.21203/rs.3.rs-4923538/v1openalex-snapshot

Rolling Bearing Fault Diagnosis Method Based on Multi-scale Convolutional Neural Network with Selective Kernel Attention Mechanism

inferred← citeshttps://doi.org/10.3390/act12040154openalex-snapshot

Intelligent Fault Diagnosis Method through ACCC-Based Improved Convolutional Neural Network

inferred← citeshttps://doi.org/10.3390/app11198967openalex-snapshot

Integrating Physics and Data Driven Cyber-Physical System for Condition Monitoring of Critical Transmission Components in Smart Production Line

inferred← citeshttps://doi.org/10.3390/app13031714openalex-snapshot

Adaptive Multi-Channel Residual Shrinkage Networks for the Diagnosis of Multi-Fault Gearbox

inferred← citeshttps://doi.org/10.3390/app14062253openalex-snapshot

Improved Adversarial Transfer Network for Bearing Fault Diagnosis under Variable Working Conditions

inferred← citeshttps://doi.org/10.3390/fractalfract8030134openalex-snapshot

A Bearing Fault Diagnosis Method under Small Sample Conditions Based on the Fractional Order Siamese Deep Residual Shrinkage Network

inferred← citeshttps://doi.org/10.3390/machines10100849openalex-snapshot

Visualized Stacked Denoising Auto-Encoder Model for Extracting and Evaluating the State Features of Rolling Bearings

inferred← citeshttps://doi.org/10.3390/machines12050305openalex-snapshot

A Fault Diagnosis Method for Key Components of the CNC Machine Feed System Based on the DoubleEnsemble–LightGBM Model

inferred← citeshttps://doi.org/10.3390/s23198060openalex-snapshot

A Novel Deep Convolutional Neural Network Combining Global Feature Extraction and Detailed Feature Extraction for Bearing Compound Fault Diagnosis

inferred← citeshttps://doi.org/10.3390/s25061775openalex-snapshot

Fault Diagnosis Method for Main Pump Motor Shielding Sleeve Based on Attention Mechanism and Multi-Source Data Fusion

inferred← citeshttps://doi.org/10.3390/s25165138openalex-snapshot

P2IFormer: A Multi-Granularity Patch-to-Image Embedding Model for Fault Diagnosis of High-Speed Train Axle-Box Bearings

inferred← citeshttps://doi.org/10.3390/sym15071413openalex-snapshot

Efficient DCNN-LSTM Model for Fault Diagnosis of Raw Vibration Signals: Applications to Variable Speed Rotating Machines and Diverse Fault Depths Datasets

inferred← citeshttps://doi.org/10.3390/vibration7040054openalex-snapshot

Vibration Signal Analysis for Intelligent Rotating Machinery Diagnosis and Prognosis: A Comprehensive Systematic Literature Review

inferred← citeshttps://doi.org/10.38007/nep.2023.040109openalex-snapshot

Taking Into Account the Practice of Using Neural Networks in Nature Conservation Environments

inferred← citeshttps://doi.org/10.54097/jceim.v10i3.8760openalex-snapshot

Review of Research on Fault Diagnosis of Rolling Bearings Based on Deep Learning

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.