On the public citation graph

Deep learning for automated drivetrain fault detection

https://doi.org/10.1002/we.2142
0 signed · 79 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1002/9780470977668openalex-snapshot
Vibration‐based Condition Monitoring
inferredcites →https://doi.org/10.1002/we.2057openalex-snapshot
Flexible non-linear predictive models for large-scale wind turbine diagnostics
inferredcites →https://doi.org/10.1002/we.319openalex-snapshot
Online wind turbine fault detection through automated SCADA data analysis
inferredcites →https://doi.org/10.1007/3-540-49430-8_9openalex-snapshot
A Dozen Tricks with Multitask Learning
inferredcites →https://doi.org/10.1007/978-0-387-45528-0openalex-snapshot
Pattern Recognition and Machine Learning
inferredcites →https://doi.org/10.1016/0041-5553(64)90137-5openalex-snapshot
Some methods of speeding up the convergence of iteration methods
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.renene.2012.04.020openalex-snapshot
Analyzing bearing faults in wind turbines: A data-mining approach
inferredcites →https://doi.org/10.1016/j.ymssp.2010.12.007openalex-snapshot
Comparative analysis of neural network and regression based condition monitoring approaches for wind turbine fault detection
inferredcites →https://doi.org/10.1038/nature16961openalex-snapshot
Mastering the game of Go with deep neural networks and tree search
inferredcites →https://doi.org/10.1109/iccv.2009.5459469openalex-snapshot
What is the best multi-stage architecture for object recognition?
inferredcites →https://doi.org/10.1109/iccv.2015.123openalex-snapshot
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
inferredcites →https://doi.org/10.1109/tii.2016.2607179openalex-snapshot
Wind Turbine Gearbox Failure Identification With Deep Neural Networks
inferredcites →https://doi.org/10.1115/1.4023516openalex-snapshot
Modeling and Prediction of Gearbox Faults With Data-Mining Algorithms
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1155/2016/4086324openalex-snapshot
Application of Artificial Neural Network for Damage Detection in Planetary Gearbox of Wind Turbine
inferredcites →https://doi.org/10.1561/2200000006openalex-snapshot
Learning Deep Architectures for AI
inferredcites →https://doi.org/10.36001/ijphm.2013.v4i3.2142openalex-snapshot
An Integrated Framework of Drivetrain Degradation Assessment and Fault Localization for Offshore Wind Turbines
inferredcites →https://doi.org/10.37052/ml.31(1)no1openalex-snapshot
What's In A Name? Malay Seals As Onomastic Sources
inferredcites →https://doi.org/10.48550/arxiv.1409.3215openalex-snapshot
Sequence to Sequence Learning with Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1603.04467openalex-snapshot
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
inferredcites →https://doi.org/10.48550/arxiv.1610.05256openalex-snapshot
Achieving Human Parity in Conversational Speech Recognition

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.4664031openalex-extracted
Supervised Deep Learning Approach for Fault Detection and Isolation in a Floating Offshore Wind Turbine Farm
inferred← citeshttps://doi.org/10.1002/aic.16497openalex-snapshot
A nonlinear support vector machine‐based feature selection approach for fault detection and diagnosis: Application to the Tennessee Eastman process
inferred← citeshttps://doi.org/10.1002/we.2290openalex-snapshot
Wind turbine gearbox failure and remaining useful life prediction using machine learning techniques
inferred← citeshttps://doi.org/10.1002/we.2352openalex-snapshot
Predictive repair scheduling of wind turbine drive‐train components based on machine learning
inferred← citeshttps://doi.org/10.1002/we.2375openalex-snapshot
Quantile regression neural network‐based fault detection scheme for wind turbines with application to monitoring a bearing
inferred← citeshttps://doi.org/10.1002/we.2856openalex-snapshot
Short‐term wind power prediction based on stacked denoised auto‐encoder deep learning and multi‐level transfer learning
inferred← citeshttps://doi.org/10.1002/we.2857openalex-snapshot
Convolutional neural network framework for wind turbine electromechanical fault detection
inferred← citeshttps://doi.org/10.1007/978-3-030-57321-8_8openalex-snapshot
Explainable Deep Learning for Fault Prognostics in Complex Systems: A Particle Accelerator Use-Case
inferred← citeshttps://doi.org/10.1007/978-3-032-26211-0_11openalex-snapshot
Fault Detection in Sensor Data Streams Using Signal Processing and Deep Learning Methods
inferred← citeshttps://doi.org/10.1007/s00170-025-17124-zopenalex-snapshot
Machine learning algorithms for optimization of bearing fault diagnosis in wind systems: a comparative study
inferred← citeshttps://doi.org/10.1007/s10916-018-0932-7openalex-snapshot
Classification of Alzheimer’s Disease Based on Eight-Layer Convolutional Neural Network with Leaky Rectified Linear Unit and Max Pooling
inferred← citeshttps://doi.org/10.1007/s11063-022-10884-9openalex-snapshot
First-order Layer in Artificial Pain Pathway
inferred← citeshttps://doi.org/10.1007/s11804-022-00298-3openalex-snapshot
Review on Artificial Intelligence-aided Life Extension Assessment of Offshore Wind Support Structures
inferred← citeshttps://doi.org/10.1016/j.apenergy.2024.124532openalex-snapshot
A clustered federated learning framework for collaborative fault diagnosis of wind turbines
inferred← citeshttps://doi.org/10.1016/j.ces.2019.07.044openalex-snapshot
Nonlinear model predictive control of a multiscale thin film deposition process using artificial neural networks
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.128926openalex-snapshot
Machine learning and hybrid intelligence for wind energy optimization: A comprehensive state-of-the-art review
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.115201openalex-snapshot
A cluster aggregation-based personalized federated learning framework for wind turbine gearbox fault diagnosis under model heterogeneity
inferred← citeshttps://doi.org/10.1016/j.measurement.2019.07.039openalex-snapshot
Vibration-based diagnostics of epicyclic gearboxes – From classical to soft-computing methods
inferred← citeshttps://doi.org/10.1016/j.measurement.2020.107735openalex-snapshot
Latest developments in gear defect diagnosis and prognosis: A review
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2024.118678openalex-snapshot
Fault detection and identification for control systems in floating offshore wind farms: A supervised Deep Learning methodology
inferred← citeshttps://doi.org/10.1016/j.renene.2020.01.042openalex-snapshot
A hybrid DBN-SOM-PF-based prognostic approach of remaining useful life for wind turbine gearbox
inferred← citeshttps://doi.org/10.1016/j.renene.2020.12.116openalex-snapshot
Fault detection and diagnosis of a blade pitch system in a floating wind turbine based on Kalman filters and artificial neural networks
inferred← citeshttps://doi.org/10.1016/j.renene.2022.04.061openalex-snapshot
A feature extraction and machine learning framework for bearing fault diagnosis
inferred← citeshttps://doi.org/10.1016/j.rser.2018.09.012openalex-snapshot
Deep Learning for fault detection in wind turbines
inferred← citeshttps://doi.org/10.1016/j.ymssp.2023.110710openalex-snapshot
Comparing torsional and lateral vibration data for deep learning-based drive train gear diagnosis
inferred← citeshttps://doi.org/10.1080/14786451.2021.1890736openalex-snapshot
Condition monitoring systems: a systematic literature review on machine-learning methods improving offshore-wind turbine operational management
inferred← citeshttps://doi.org/10.1080/14786451.2024.2326296openalex-snapshot
A review of artificial intelligence applications in wind turbine health monitoring
inferred← citeshttps://doi.org/10.1088/1742-6596/3166/1/012006openalex-snapshot
EMF-Net: An End-to-End Intelligent Detection Architecture for Welding Defects in Complex Industrial Scenarios
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.2022.3219480openalex-snapshot
Deep Learning Approach for Sensor Data Prediction and Sensor Fault Diagnosis in Wind Turbine Blade
inferred← citeshttps://doi.org/10.1109/access.2025.3627885openalex-snapshot
Rapid Deployment of Deep Learning-Based Condition Monitoring for Rotating Machines
inferred← citeshttps://doi.org/10.1109/aim43001.2020.9158977openalex-snapshot
Drivetrain System Identification in a Multi-Task Learning Strategy using Partial Asynchronous Elastic Averaging Stochastic Gradient Descent
inferred← citeshttps://doi.org/10.1109/gcitc60406.2023.10426295openalex-snapshot
Count Based Analysis of PCOM Using Blob-Based Detection Method in 2D Ultrasound Images of Ovary
inferred← citeshttps://doi.org/10.1109/icmla.2019.00172openalex-snapshot
Evaluating Unsupervised Anomaly Detection Models to Detect Faults in Heavy Haul Railway Operations
inferred← citeshttps://doi.org/10.1109/icpes63746.2024.10856617openalex-snapshot
Research About the Impact of Cms on the Reliability of Wind Turbines in Application Scenarios
inferred← citeshttps://doi.org/10.1109/icphm.2018.8448450openalex-snapshot
Tandem Connectionist Anomaly Detection: Use of Faulty Vibration Signals in Feature Representation Learning
inferred← citeshttps://doi.org/10.1109/icphm.2019.8819396openalex-snapshot
Visual explanation of neural network based rotation machinery anomaly detection system
inferred← citeshttps://doi.org/10.1109/icrms55680.2022.9944585openalex-snapshot
Deployable Lightweight ANN-based Approach for Wind Turbine Fault Detection
inferred← citeshttps://doi.org/10.1109/iecon43393.2020.9255330openalex-snapshot
An artificial intelligence approach to fault isolation based on sensor data in Tennessee Eastman process
inferred← citeshttps://doi.org/10.1109/ijcnn55064.2022.9892755openalex-snapshot
Detection of bearing failures using wavelet transformation and machine learning approach
inferred← citeshttps://doi.org/10.1109/itsc.2018.8569908openalex-snapshot
Pre-ignition Detection Using Deep Neural Networks: A Step Towards Data-driven Automotive Diagnostics
inferred← citeshttps://doi.org/10.1145/3586006openalex-snapshot
Deep Learning for Variable Renewable Energy: A Systematic Review
inferred← citeshttps://doi.org/10.1155/2019/6921975openalex-snapshot
Fault Diagnosis of Reciprocating Compressor Based on Convolutional Neural Networks with Multisource Raw Vibration Signals
inferred← citeshttps://doi.org/10.1155/2020/8843759openalex-snapshot
A Review of Artificial Intelligence Methods for Condition Monitoring and Fault Diagnosis of Rolling Element Bearings for Induction Motor
inferred← citeshttps://doi.org/10.1177/0309524x261423723openalex-snapshot
Machine learning applications in wind energy production: Current status, challenges, and future directions
inferred← citeshttps://doi.org/10.21203/rs.3.rs-7377871/v1openalex-snapshot
AI-Augmented FEA for Offshore Wind Turbine Equipment: A State-of-the-Art Methodology for Accelerated Fabrication Review
inferred← citeshttps://doi.org/10.2478/pomr-2024-0011openalex-snapshot
Fault Diagnosis of Imbalance and Misalignment in Rotor-Bearing Systems Using Deep Learning
inferred← citeshttps://doi.org/10.26748/ksoe.2021.018openalex-snapshot
Fault Classification of a Blade Pitch System in a Floating Wind Turbine Based on a Recurrent Neural Network
inferred← citeshttps://doi.org/10.3389/fenrg.2021.799039openalex-snapshot
Monitoring and Identifying Wind Turbine Generator Bearing Faults Using Deep Belief Network and EWMA Control Charts
inferred← citeshttps://doi.org/10.3390/electronics9091513openalex-snapshot
A Survey on Active Fault-Tolerant Control Systems
inferred← citeshttps://doi.org/10.3390/en13030584openalex-snapshot
Condition Monitoring in Photovoltaic Systems by Semi-Supervised Machine Learning
inferred← citeshttps://doi.org/10.3390/en13123132openalex-snapshot
Using SCADA Data for Wind Turbine Condition Monitoring: A Systematic Literature Review
inferred← citeshttps://doi.org/10.3390/jmse13091638openalex-snapshot
Anomaly-Detection Framework for Thrust Bearings in OWC WECs Using a Feature-Based Autoencoder
inferred← citeshttps://doi.org/10.3390/s20092710openalex-snapshot
Deep Learning-Based Real-Time Auto Classification of Smartphone Measured Bridge Vibration Data
inferred← citeshttps://doi.org/10.36001/phme.2020.v5i1.1217openalex-snapshot
Early Fault Detection Based on Wind Turbine SCADA Data Using Convolutional Neural Networks
inferred← citeshttps://doi.org/10.5539/ijbm.v19n3p1openalex-snapshot
Optimization Models for Operations and Maintenance of Offshore Wind Turbines Based on Artificial Intelligence and Operations Research: A Systematic Literature Review
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.