Early Fault Detection on CMAPSS with Unsupervised LSTM Autoencoders
Fuente:
arXiv
Saved in:
| Main Authors: | Sánchez, P., Reyes, K., Radu, B., Fernández, E. |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LSTM VS. Feed-Forward Autoencoders for Unsupervised Fault Detection in Hydraulic Pumps
by: Sánchez, P., et al.
Published: (2026)
by: Sánchez, P., et al.
Published: (2026)
Assesing the Viability of Unsupervised Learning with Autoencoders for Predictive Maintenance in Helicopter Engines
by: Sánchez, P., et al.
Published: (2026)
by: Sánchez, P., et al.
Published: (2026)
A Physics-Aware Attention LSTM Autoencoder for Early Fault Diagnosis of Battery Systems
by: Yang, Jiong
Published: (2025)
by: Yang, Jiong
Published: (2025)
Unsupervised High Impedance Fault Detection Using Autoencoder and Principal Component Analysis
by: Liu, Yingxiang, et al.
Published: (2023)
by: Liu, Yingxiang, et al.
Published: (2023)
Hybrid Autoencoder-Based Framework for Early Fault Detection in Wind Turbines
by: Nair, Rekha R, et al.
Published: (2025)
by: Nair, Rekha R, et al.
Published: (2025)
Fault Detection in Electrical Distribution System using Autoencoders
by: Nayak, Sidharthenee, et al.
Published: (2026)
by: Nayak, Sidharthenee, et al.
Published: (2026)
Comparative Evaluation of Kolmogorov-Arnold Autoencoders and Orthogonal Autoencoders for Fault Detection with Varying Training Set Sizes
by: Villagómez, Enrique Luna, et al.
Published: (2025)
by: Villagómez, Enrique Luna, et al.
Published: (2025)
Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction
by: Üstek, İrem, et al.
Published: (2024)
by: Üstek, İrem, et al.
Published: (2024)
Unsupervised Out-of-Distribution Detection by Restoring Lossy Inputs with Variational Autoencoder
by: Zeng, Zezhen, et al.
Published: (2023)
by: Zeng, Zezhen, et al.
Published: (2023)
Unveiling Multiple Descents in Unsupervised Autoencoders
by: Rahimi, Kobi, et al.
Published: (2024)
by: Rahimi, Kobi, et al.
Published: (2024)
Exploiting temporal parallelism for LSTM Autoencoder acceleration on FPGA
by: Leftheriotis, Aimilios, et al.
Published: (2026)
by: Leftheriotis, Aimilios, et al.
Published: (2026)
Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection
by: Liao, Jing-Xiao, et al.
Published: (2022)
by: Liao, Jing-Xiao, et al.
Published: (2022)
Quorum: Zero-Training Unsupervised Anomaly Detection using Quantum Autoencoders
by: Ludmir, Jason Zev, et al.
Published: (2025)
by: Ludmir, Jason Zev, et al.
Published: (2025)
Spatial-Temporal Bearing Fault Detection Using Graph Attention Networks and LSTM
by: Singh, Moirangthem Tiken, et al.
Published: (2024)
by: Singh, Moirangthem Tiken, et al.
Published: (2024)
Hybrid Quantum-Classical Autoencoders for Unsupervised Network Intrusion Detection
by: Rasyidi, Mohammad Arif, et al.
Published: (2025)
by: Rasyidi, Mohammad Arif, et al.
Published: (2025)
Attention and Autoencoder Hybrid Model for Unsupervised Online Anomaly Detection
by: Najafi, Seyed Amirhossein, et al.
Published: (2024)
by: Najafi, Seyed Amirhossein, et al.
Published: (2024)
Learnable Faster Kernel-PCA for Nonlinear Fault Detection: Deep Autoencoder-Based Realization
by: Ren, Zelin, et al.
Published: (2021)
by: Ren, Zelin, et al.
Published: (2021)
LSTM Autoencoder-based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction
by: Wang, Guanjin, et al.
Published: (2024)
by: Wang, Guanjin, et al.
Published: (2024)
Unsupervised Deep Clustering of MNIST with Triplet-Enhanced Convolutional Autoencoders
by: Ansari, Md. Faizul Islam
Published: (2025)
by: Ansari, Md. Faizul Islam
Published: (2025)
Unsupervised Fault Detection using SAM with a Moving Window Approach
by: Maged, Ahmed, et al.
Published: (2024)
by: Maged, Ahmed, et al.
Published: (2024)
Generative Pre-Training of Time-Series Data for Unsupervised Fault Detection in Semiconductor Manufacturing
by: Lee, Sewoong, et al.
Published: (2023)
by: Lee, Sewoong, et al.
Published: (2023)
Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data
by: Saha, Snehanshu, et al.
Published: (2023)
by: Saha, Snehanshu, et al.
Published: (2023)
Unsupervised Feature Selection via Robust Autoencoder and Adaptive Graph Learning
by: Yu, Feng, et al.
Published: (2025)
by: Yu, Feng, et al.
Published: (2025)
Double-Adversarial Activation Anomaly Detection: Adversarial Autoencoders are Anomaly Generators
by: Schulze, J. -P., et al.
Published: (2021)
by: Schulze, J. -P., et al.
Published: (2021)
Towards Unsupervised Causal Representation Learning via Latent Additive Noise Model Causal Autoencoders
by: Ong, Hans Jarett J., et al.
Published: (2025)
by: Ong, Hans Jarett J., et al.
Published: (2025)
An Unsupervised Adversarial Autoencoder for Cyber Attack Detection in Power Distribution Grids
by: Zideh, Mehdi Jabbari, et al.
Published: (2024)
by: Zideh, Mehdi Jabbari, et al.
Published: (2024)
Safety Enhancement in Planetary Rovers: Early Detection of Tip-over Risks Using Autoencoders
by: Alvarez, Mariela De Lucas
Published: (2024)
by: Alvarez, Mariela De Lucas
Published: (2024)
Unsupervised Multi-Attention Meta Transformer for Rotating Machinery Fault Diagnosis
by: Wang, Hanyang, et al.
Published: (2025)
by: Wang, Hanyang, et al.
Published: (2025)
PICore: Physics-Informed Unsupervised Coreset Selection for Data Efficient Neural Operator Training
by: Satheesh, Anirudh, et al.
Published: (2025)
by: Satheesh, Anirudh, et al.
Published: (2025)
Explainable Unsupervised Multi-Anomaly Detection and Temporal Localization in Nuclear Times Series Data with a Dual Attention-Based Autoencoder
by: Vasili, Konstantinos, et al.
Published: (2025)
by: Vasili, Konstantinos, et al.
Published: (2025)
Credit Card Fraud Detection in the Nigerian Financial Sector: A Comparison of Unsupervised TensorFlow-Based Anomaly Detection Techniques, Autoencoders and PCA Algorithm
by: Onyeama, Jennifer
Published: (2024)
by: Onyeama, Jennifer
Published: (2024)
Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery
by: Gopalakrishnan, Anand, et al.
Published: (2024)
by: Gopalakrishnan, Anand, et al.
Published: (2024)
Autoencoder-assisted Feature Ensemble Net for Incipient Faults
by: Gao, Mingxuan, et al.
Published: (2024)
by: Gao, Mingxuan, et al.
Published: (2024)
Kolmogorov-Arnold Networks-based GRU and LSTM for Loan Default Early Prediction
by: Yang, Yue, et al.
Published: (2025)
by: Yang, Yue, et al.
Published: (2025)
Hybrid Efficient Unsupervised Anomaly Detection for Early Pandemic Case Identification
by: Ghajari, Ghazal, et al.
Published: (2024)
by: Ghajari, Ghazal, et al.
Published: (2024)
PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders
by: Xie, Tianyu, et al.
Published: (2025)
by: Xie, Tianyu, et al.
Published: (2025)
Out-of-Distribution Radar Detection in Compound Clutter and Thermal Noise through Variational Autoencoders
by: Rouzoumka, Y A, et al.
Published: (2025)
by: Rouzoumka, Y A, et al.
Published: (2025)
Steam Turbine Anomaly Detection: An Unsupervised Learning Approach Using Enhanced Long Short-Term Memory Variational Autoencoder
by: Xu, Weiming, et al.
Published: (2024)
by: Xu, Weiming, et al.
Published: (2024)
Early Prediction of Sepsis using Heart Rate Signals and Genetic Optimized LSTM Algorithm
by: Rafiei, Alireza, et al.
Published: (2025)
by: Rafiei, Alireza, et al.
Published: (2025)
CL-MAE: Curriculum-Learned Masked Autoencoders
by: Madan, Neelu, et al.
Published: (2023)
by: Madan, Neelu, et al.
Published: (2023)
Similar Items
-
LSTM VS. Feed-Forward Autoencoders for Unsupervised Fault Detection in Hydraulic Pumps
by: Sánchez, P., et al.
Published: (2026) -
Assesing the Viability of Unsupervised Learning with Autoencoders for Predictive Maintenance in Helicopter Engines
by: Sánchez, P., et al.
Published: (2026) -
A Physics-Aware Attention LSTM Autoencoder for Early Fault Diagnosis of Battery Systems
by: Yang, Jiong
Published: (2025) -
Unsupervised High Impedance Fault Detection Using Autoencoder and Principal Component Analysis
by: Liu, Yingxiang, et al.
Published: (2023) -
Hybrid Autoencoder-Based Framework for Early Fault Detection in Wind Turbines
by: Nair, Rekha R, et al.
Published: (2025)