Imagen de Portada

A Physics-Aware Attention LSTM Autoencoder for Early Fault Diagnosis of Battery Systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Yang, Jiong
Formato:	Preprint
Publicado:	2025
Materias:	Systems and Control Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Ensemble-Enhanced Graph Autoencoder with GAT and Transformer-Based Encoders for Robust Fault Diagnosis
por: Singh, Moirangthem Tiken
Publicado: (2025)

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

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

Integrating LLMs for Explainable Fault Diagnosis in Complex Systems
por: Dave, Akshay J., et al.
Publicado: (2024)

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

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

Autoencoder-assisted Feature Ensemble Net for Incipient Faults
por: Gao, Mingxuan, et al.
Publicado: (2024)

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

Asymmetric Adaptation-based Real-time Fault Diagnosis Under Transitional Operating Conditions
por: Zhao, Hongshuo, et al.
Publicado: (2026)

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

Avionic Main Fuel Pump Simulation and Fault-Diagnosis Benchmark
por: Janzen, Felix Leonhard, et al.
Publicado: (2026)

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

Shapley-based Explainable AI for Clustering Applications in Fault Diagnosis and Prognosis
por: Cohen, Joseph, et al.
Publicado: (2023)

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

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

Prognosis Of Lithium-Ion Battery Health with Hybrid EKF-CNN+LSTM Model Using Differential Capacity
por: Hoque, Md Azizul, et al.
Publicado: (2025)

A Multimodal Lightweight Approach to Fault Diagnosis of Induction Motors in High-Dimensional Dataset
por: Ali, Usman
Publicado: (2025)

Padé Approximant Neural Networks for Enhanced Electric Motor Fault Diagnosis Using Vibration and Acoustic Data
por: Kilickaya, Sertac, et al.
Publicado: (2025)

A Trustworthy Industrial Fault Diagnosis Architecture Integrating Probabilistic Models and Large Language Models
por: wu, Yue
Publicado: (2025)

Advanced Hybrid Transformer LSTM Technique with Attention and TS Mixer for Drilling Rate of Penetration Prediction
por: Khan, Saddam Hussain
Publicado: (2025)

Learning Automata of PLCs in Production Lines Using LSTM
por: AlTalafha, Iyas, et al.
Publicado: (2025)

FM-CAC: Carbon-Aware Control for Battery-Buffered Edge AI via Time-Series Foundation Models
por: Yang, Kang, et al.
Publicado: (2026)

Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders
por: Sundsgaard, Konrad, et al.
Publicado: (2025)

Real-Time Vibration-Based Bearing Fault Diagnosis Under Time-Varying Speed Conditions
por: Jalonen, Tuomas, et al.
Publicado: (2023)

Lab-scale Vibration Analysis Dataset and Baseline Methods for Machinery Fault Diagnosis with Machine Learning
por: Atmaja, Bagus Tris, et al.
Publicado: (2022)

Advancing Gasoline Consumption Forecasting: A Novel Hybrid Model Integrating Transformers, LSTM, and CNN
por: Ranjbar, Mahmoud, et al.
Publicado: (2024)

Hybrid Energy-Aware Reward Shaping: A Unified Lightweight Physics-Guided Methodology for Policy Optimization
por: Liao, Qijun, et al.
Publicado: (2026)

Multivariate Physics-Informed Convolutional Autoencoder for Anomaly Detection in Power Distribution Systems with High Penetration of DERs
por: Zideh, Mehdi Jabbari, et al.
Publicado: (2024)

Stability Enhanced Gaussian Process Variational Autoencoders
por: Richardson, Carl R., et al.
Publicado: (2026)

Hybrid LSTM-UKF Framework: Ankle Angle and Ground Reaction Force Estimation
por: Narasimhappa, Mundla, et al.
Publicado: (2026)

Latency-Aware Deep Learning Benchmark for Real-Time Cyber-Physical Attack and Fault Classification in Inverter-Dominated Power Grids
por: Abukhousa, Emad, et al.
Publicado: (2026)

Asymmetric-Loss-Guided Hybrid CNN-BiLSTM-Attention Model for Industrial RUL Prediction with Interpretable Failure Heatmaps
por: Abdullah, Mohammed Ezzaldin Babiker
Publicado: (2026)

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

TRIZ Method for Urban Building Energy Optimization: GWO-SARIMA-LSTM Forecasting model
por: Zheng, Shirong, et al.
Publicado: (2024)

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

FaultXformer: A Transformer-Encoder Based Fault Classification and Location Identification model in PMU-Integrated Active Electrical Distribution System
por: Thakur, Kriti, et al.
Publicado: (2026)

Adaptive Cyber-Attack Detection in IIoT Using Attention-Based LSTM-CNN Models
por: Gueriani, Afrah, et al.
Publicado: (2025)

Bridging Autoencoders and Dynamic Mode Decomposition for Reduced-order Modeling and Control of PDEs
por: Saha, Priyabrata, et al.
Publicado: (2024)

Discovering Nonlinear Static Relationships in Unlabeled Dataset using Autoencoder with Ordered Variance
por: Augustine, Midhun T., et al.
Publicado: (2024)

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