Cover Image

Fault Detection in New Wind Turbines with Limited Data by Generative Transfer Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jonas, Stefan, Meyer, Angela
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Wind turbine condition monitoring based on intra- and inter-farm federated learning
by: Grataloup, Albin, et al.
Published: (2024)

Condition Monitoring with Machine Learning: A Data-Driven Framework for Quantifying Wind Turbine Energy Loss
by: Buchberg, Emil Marcus, et al.
Published: (2025)

Adversarial Sensor Errors for Safe and Robust Wind Turbine Fleet Control
by: Quick, Julian, et al.
Published: (2026)

A review of federated learning in renewable energy applications: Potential, challenges, and future directions
by: Grataloup, Albin, et al.
Published: (2023)

Generalizable Temperature Nowcasting with Physics-Constrained RNNs for Predictive Maintenance of Wind Turbine Components
by: Exenberger, Johannes, et al.
Published: (2024)

BUILDA: A Thermal Building Data Generation Framework for Transfer Learning
by: Krug, Thomas, et al.
Published: (2025)

Active Learning-Based Optimization of Hydroelectric Turbine Startup to Minimize Fatigue Damage
by: Mai, Vincent, et al.
Published: (2024)

Fault Detection in Electrical Distribution System using Autoencoders
by: Nayak, Sidharthenee, et al.
Published: (2026)

Fault Detection in Solar Thermal Systems using Probabilistic Reconstructions
by: Ebmeier, Florian, et al.
Published: (2025)

Runtime Monitoring and Fault Detection for Neural Network-Controlled Systems
by: Lan, Jianglin, et al.
Published: (2024)

Learning to Optimise Wind Farms with Graph Transformers
by: Li, Siyi, et al.
Published: (2023)

PPGN: Physics-Preserved Graph Networks for Real-Time Fault Location in Distribution Systems with Limited Observation and Labels
by: Li, Wenting, et al.
Published: (2021)

Learning a Factorized Orthogonal Latent Space using Encoder-only Architecture for Fault Detection; An Alarm management perspective
by: Eivaghi, Vahid MohammadZadeh, et al.
Published: (2024)

Fundamental Limits of Man-in-the-Middle Attack Detection in Model-Free Reinforcement Learning
by: Rani, Rishi, et al.
Published: (2026)

Wind Power Scenario Generation based on the Generalized Dynamic Factor Model and Generative Adversarial Network
by: Cho, Young-ho, et al.
Published: (2025)

Transfer Learning Assisted XgBoost For Adaptable Cyberattack Detection In Battery Packs
by: Ghosh, Sanchita, et al.
Published: (2025)

Unsupervised High Impedance Fault Detection Using Autoencoder and Principal Component Analysis
by: Liu, Yingxiang, et al.
Published: (2023)

Fault Diagnosis and Prognosis Capabilities for Wind Turbine Hydraulic Pitch Systems
by: Dallabona, Alessio, et al.
Published: (2023)

Physics-Informed Deep Learning and Partial Transfer Learning for Bearing Fault Diagnosis in the Presence of Highly Missing Data
by: Kavianpour, Mohammadreza, et al.
Published: (2024)

Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits
by: Maity, Sreejeet, et al.
Published: (2025)

Learn to Bid as a Price-Maker Wind Power Producer
by: Singhal, Shobhit, et al.
Published: (2025)

Marginalize, Rather than Impute: Probabilistic Wind Power Forecasting with Incomplete Data
by: Wen, Honglin, et al.
Published: (2024)

Learnable Faster Kernel-PCA for Nonlinear Fault Detection: Deep Autoencoder-Based Realization
by: Ren, Zelin, et al.
Published: (2021)

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis
by: Khan, Abdullah, et al.
Published: (2024)

Multi-Agent Based Transfer Learning for Data-Driven Air Traffic Applications
by: Deng, Chuhao, et al.
Published: (2024)

Fault Diagnosis on Induction Motor using Machine Learning and Signal Processing
by: Samiullah, Muhammad, et al.
Published: (2024)

Accelerating Reinforcement Learning for Wind Farm Control via Expert Demonstrations
by: Nilsen, Marcus Binder, et al.
Published: (2026)

GenTL: A General Transfer Learning Model for Building Thermal Dynamics
by: Raisch, Fabian, et al.
Published: (2025)

Fault Detection and Identification Using a Novel Process Decomposition Algorithm for Distributed Process Monitoring
by: Villagomez, Enrique Luna, et al.
Published: (2024)

From Big Data to Fast Data: Towards High-Quality Datasets for Machine Learning Applications from Closed-Loop Data Collection
by: Reis, Philipp, et al.
Published: (2026)

WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
by: Monroc, Claire Bizon, et al.
Published: (2025)

Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning
by: Nauck, Christian, et al.
Published: (2024)

Review on Fault Diagnosis and Fault-Tolerant Control Scheme for Robotic Manipulators: Recent Advances in AI, Machine Learning, and Digital Twin
by: Quamar, Md Muzakkir, et al.
Published: (2024)

Clustered Federated Learning for Generalizable FDIA Detection in Smart Grids with Heterogeneous Data
by: Li, Yunfeng, et al.
Published: (2025)

Graph Neural Networks in Wind Power Forecasting
by: Castellano, Javier, et al.
Published: (2025)

Learning Generative Models for Climbing Aircraft from Radar Data
by: Pepper, Nick, et al.
Published: (2023)

The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning
by: Abukhousa, Emad, et al.
Published: (2025)

Supervised Transfer Learning Framework for Fault Diagnosis in Wind Turbines
by: Weber, Kenan, et al.
Published: (2024)

AI-Powered Dynamic Fault Detection and Performance Assessment in Photovoltaic Systems
by: Salazar-Pena, Nelson, et al.
Published: (2024)

Transfer Learning for Control Systems via Neural Simulation Relations
by: Nadali, Alireza, et al.
Published: (2024)