About the Journal
		The European Conference of the Prognostics and Health Management (PHM) Society is held in the spring of even years (starting in 2012) and brings together the global community of PHM experts from industry, academia, and government in diverse application areas including energy, aerospace, transportation, automotive, manufacturing, and industrial automation.
All articles published by the PHM Society are available to the global PHM community via the internet for free and without any restrictions.
Current Issue
Proceedings Front Matter
PHME 2024 Management Team and Publisher Information
Technical Papers
A Comparative Study of Semi-Supervised Anomaly Detection Methods for Machine Fault Detection
					Page 10
					
						
				
A Computer Vision Deep Learning Tool for Automatic Recognition of Bearing Failure Modes
					Page 5
					
						
				
A data-driven risk assessment approach for electronic boards used in oil well drilling operations
					Page 8
					
						
				
A Flexible Methodology for Uncertainty-Quantified Monitoring of Abrasive Wear in Heavy Machinery Using Neural Networks and Phenomenology-Based Feature Engineering
					Page 9
					
						
				
A Gear Health Indicator Based on f-AnoGAN
					Page 12
					
						
				
A Hybrid – Machine Learning and Possibilistic – Methdology for Predicting Produced Power Using Wind Turbine SCADA Data
					Page 15
					
						
				
A maturity framework for data driven maintenance
A Novel Approach for Evaluating Datasets Similarities Based on Analytical Hierarchy Process in the Industrial PHM Context
					Page 10
					
						
				
A PHM implementation frame work for MASS (Maritime Autonomous Surface Ships) based on RAM (Reliability Availability Maintainability)
					Page 16
					
						
				
A Physics-Inspired and Data-Driven Approach for Temperature-Based Condition Monitoring
					Page 10
					
						
				
A Practical Example of Applying Machine Learning to a Real Turbofan Engine Issue: NEOP
					Page 7
					
						
				
A Review of Prognostics and Health Management in Wind Turbine Components
					Page 15
					
						
				
A rolling bearing state evaluation method based on deep learning combined with Wiener process
					Page 8
					
						
				
A Semi-supervised Fault Diagnosis Method Based on Graph Convolution for Few-shot Fault Diagnosis
					Page 8
					
						
				
A Study on the Equipment Data Collection and Developing Next Generation Integrated PHM System
					Page 7
					
						
				
Active learning for gear defect detection in gearboxes
					Page 10
					
						
				
Advancing Durability Testing in Automotive Component through Prognostics and Health Management (PHM) Integration
					Page 6
					
						
				
An Experiment on Anomaly Detection for Fault Vibration Signals Using Autoencoder-Based N-Segmentation Algorithm
					Page 8
					
						
				
Analytical Modeling of Health Indices for Prognostics and Health Management
					Page 11
					
						
				
Anomaly Detection of a Cooling Water Pump of a Power Plant Based on its Virtual Digital Twin Constructed with Deep Learning Techniques
					Page 9
					
						
				
Applying Prognostics and Health Management to Optimize Safety and Sustainability at the First Adaptive High-Rise Structure
					Page 12
					
						
				
Automated Fault Diagnosis Using Maximal Overlap Discret Wavelet Packet Transform and Principal Components Analysis
					Page 7
					
						
				
Bayesian Networks for Remaining Useful Life Prediction
					Page 11
					
						
				
Characterizing Damage in Wind Turbine Mooring Using a Data-Driven Predictor Model within a Particle Filtering Estimation Framework
					Page 8
					
						
				
Comparison among Machine Learning Models Applied in Lithiumion Battery Internal Short Circuit Detection
					Page 10
					
						
				
Continuous Test-time Domain Adaptation for Efficient Fault Detection under Evolving Operating Conditions
					Page 11
					
						
				
Contrastive Metric Learning Loss-Enhanced Multi-Layer Perceptron for Sequentially Appearing Clusters in Acoustic Emission Data Streams
					Page 10
					
						
				
Counterfactual Explanation for Auto-Encoder Based Time-Series Anomaly Detection
					Page 9
					
						
				
Damage Detection using Machine Learning for PHM in Gearbox Applications
					Page 12
					
						
				
Data Scarcity in Fault Detection for Solar Tracking Systems: the Power of Physics-Informed Artificial Intelligence
					Page 8
					
						
				
Data-Driven Prognostics with Multi-Layer Perceptron Particle Filter: a Cross-Industry Exploration
					Page 8
					
						
				
Data-Driven Remaining Useful Life Estimation Approach for Neutron Generators in Multifunction Logging-While-Drilling Service
Defect Data Augmentation Method for Robust Image-based Product Inspection
					Page 8
					
						
				
Detection of Abnormal Conditions in Electro-Mechanical Actuators by Physics-Informed Long Short-term Memory Networks
					Page 8
					
						
				
Development of a Feature Extraction Methodology for Prognostic Tasks of Aerospace Structures and Systems
					Page 11
					
						
				
Development of a PHM system for electrically actuated brakes of a smallpassenger aircraft
					Page 12
					
						
				
Development of Anomaly Detection Technology Applicable to Various Equipment Groups in Smart Factory
					Page 12
					
						
				
Development of Fault Diagnosis Model based on Semi-supervised Autoencoder
					Page 7
					
						
				
DiffPhysiNet: A Bearing Diagnostic Framework Based on Physics-Driven Diffusion Network for Unseen Working Conditions
					Page 10
					
						
				
Domain Adaptation for Fault Detection in Civil Nuclear Plants
					Page 11
					
						
				
Domain Adaptation via Simulation Parameter and Data Perturbation for Predictive Maintenance
					Page 11
					
						
				
Dynamic Modeling of Distributed Wear-Like Faults in Spur Gears: Simplified Approach with Experimental Validation
					Page 7
					
						
				
Enhanced Diagnostics Empowered by Improved Mechanical Vibration Component Extraction in Nonstationary Regimes
					Page 10
					
						
				
Enhancing Data-driven Vibration-based Machinery Fault Diagnosis Generalization Under Varied Conditions by Removing Domain-Specific Information Utilizing Sparse Representation
					Page 7
					
						
				
Enhancing gearbox condition monitoring using randomized singular value decomposition and K-nearest neighbor
					Page 7
					
						
				
Enhancing Lithium-ion Battery Safety: Analysis and Detection of Internal Short Circuit basing on an Electrochemical-Thermal Modeling
					Page 7
					
						
				
Enhancing Lithium-Ion Battery State-of-Charge Estimation Across Battery Types via Unsupervised Domain Adaptation
					Page 8
					
						
				
Exploring a Knowledge-Based Approach for Predictive Maintenance of Aircraft Engines: Studying Fault Propagation through Spatial and Topological Component Relationships
					Page 9
					
						
				
False alarm reduction in railway track quality inspections using machine learning
					Page 8
					
						
				
Fault Diagnosis of Multiple Components in Complex Mechanical System Using Remote Sensor
					Page 9
					
						
				
Fault Prediction and Estimation of Automotive LiDAR Signals Using Transfer Learning-Based Domain Generalization
					Page 6
					
						
				
From Prediction to Prescription: Large Language Model Agent for Context-Aware Maintenance Decision Support
					Page 10
					
						
				
Fully Automated Diagnostics of Induction Motor Drives in Offshore Wind Turbine Pitch Systems using Extended Park Vector Transform and Convolutional Neural Network
					Page 11
					
						
				
Graph Neural Networks for Electric and Hydraulic Data Fusion to Enhance Short-term Forecasting of Pumped-storage Hydroelectricity
					Page 11
					
						
				
Health-aware Control for Health Management of Lithium-ion Battery in a V2G Scenario
					Page 10
					
						
				
Human-Centric PHM in the Era of Industry 5.0
					Page 7
					
						
				
Hybrid AI-Subject Matter Expert Solution for Evaluating the Health Index of Oil Distribution Transformers
					Page 8
					
						
				
Hybrid Prognostics for Aircraft Fuel System: An Approach to Forecasting the Future
					Page 9
					
						
				
Influence of Reducing the Load Level of Mission Profiles on the Remaining Useful Life of a TO220 Analyzed with a Surrogate Model
					Page 6
					
						
				
Integrating Network Theory and SHAP Analysis for Enhanced RUL Prediction in Aeronautics
					Page 15
					
						
				
Integration of Condition Information in UAV Swarm Management to increase System Availability in dynamic Environments
					Page 11
					
						
				
Labeling Algorithm for Outer-Race Faults in Bearings Based on Load Signal
					Page 7
					
						
				
Landing Gear Health Assessment: Synergising Flight Data Analysis with Theoretical Prognostics in a Hybrid Assessment Approach
					Page 10
					
						
				
Large Language Model-based Chatbot for Improving Human-Centricity in Maintenance Planning and Operations
					Page 12
					
						
				
Leveraging Generative and Probabilistic Models for Diagnostics of Cyber-Physical Systems
					Page 7
					
						
				
LSTM and Transformers based methods for Remaining Useful Life Prediction considering Censored Data
					Page 10
					
						
				
Maintenance decision-making model for gas turbine engine components
					Page 7
					
						
				
Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning
					Page 14
					
						
				
Model-based Probabilistic Diagnosis in Large Cyberphysical Systems
					Page 12
					
						
				
MOXAI – Manufacturing Optimization through Model-Agnostic Explainable AI and Data-Driven Process Tuning
					Page 7
					
						
				
NLP-Based Fault Detection Method for Multifunction Logging-While-Drilling Services
Noise-aware AI methods for robust acoustic monitoring of bearings in industrial machines
					Page 10
					
						
				
On the Feasibility of Condition Monitoring of Belt Splices in Belt Conveyor Systems Using IoT Devices*
					Page 7
					
						
				
Particle Filter Approach for Prognostics Using Exact Static Parameter Estimation and Consistent Prediction
					Page 10
					
						
				
PHM for Spacecraft Propulsion Systems: Developing Resilient Models for Real-World Challenges
					Page 7
					
						
				
Probabilistic Uncertainty-Aware Decision Fusion of Neural Network for Bearing Fault Diagnosis
					Page 10
					
						
				
Prognosis of Internal Short Circuit Formation in Lithium-Ion Batteries: An Integrated Approach Using Extended Kalman Filter and Regression Model
					Page 8
					
						
				
Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions
					Page 9
					
						
				
Residual Selection for Observer-Based Fault Detection and Isolation in a Multi-Engine Propulsion Cluster
					Page 9
					
						
				
Robust Remaining Useful Life Prediction Using Jacobian Feature Regression-Based Model Adaptation
					Page 11
					
						
				
Simulation-based remaining useful life prediction of rolling element bearings under varying operating conditions
					Page 12
					
						
				
Soft Ordering 1-D CNN to Estimate the Capacity Factor of Windfarms for Identifying the Age-Related Performance Degradation
					Page 9
					
						
				
State-of-Charge and State-of-Health Estimation for Li-Ion Batteries of Hybrid Electric Vehicles under Deep Degradation
					Page 10
					
						
				
Statistical Knowledge Integration into Neural Networks: Novel Neuron Units for Bearing Prognostics
					Page 14
					
						
				
SurvLoss: A New Survival Loss Function for Neural Networks to Process Censored Data
					Page 7
					
						
				
System-level Probabilistic Remaining Useful Life Prognostics and Predictive Inspection Planning for Wind Turbines
					Page 13
					
						
				
Testing Topological Data Analysis for Condition Monitoring of Wind Turbines
					Page 10
					
						
				
Test-Training Leakage in Evaluation of Machine Learning Algorithms for Condition-Based Maintenance
					Page 13
					
						
				
Timeseries Feature Extraction for Dataset Creation in Prognostic Health Management
					Page 13
					
						
				
Towards a Hybrid Framework for Prognostics with Limited Run-to-Failure Data
					Page 12
					
						
				
Towards a Probabilistic Fusion Approach for Robust Battery Prognostics
					Page 13
					
						
				
Towards Efficient Operation and Maintenance of Wind Farms: Leveraging AI for Minimizing Human Error
					Page 9
					
						
				
Towards Physics-Informed PHM for Multi-component degradation (MCD) in complex systems
					Page 14
					
						
				
Transfer Learning-based Adaptive Diagnosis for Power Plants under Varying Operating Conditions
					Page 6
					
						
				
Ultrafast laser damaging of ball bearings for the condition monitoring of a fleet of linear motors
					Page 10
					
						
				
Uncertainty in Aircraft Turbofan Engine Prognostics on the C-MAPSS Dataset
					Page 10
					
						
				
Unsupervised Learning for Bearing Fault Identification with Vibration Data
					Page 9
					
						
				
Virtual Sensor for Real-Time Bearing Load Prediction Using Heterogeneous Temporal Graph Neural Networks
					Page 8
					
						
				
Posters
A novel prognostics solution for accurate identification of degradation patterns in turbo machines with variable observation window
Case Study of Product Development through Generative Design according to Anemometer Replacement Cycles
Feature Selection Method for Gear Health Indicator Using MIC Ranking
					Page 8
					
						
				
Filter-based feature selection for prognostics incorporating cross correlations and failure thresholds
					Page 10
					
						
				
Integrated design of negative stiffness honeycomb structures considering performance and operational degradation
					Page 12
					
						
				
Mastering Training Data Generation for AI - Integrating High- Fidelity Component Models with Standard Flight Simulator Software
					Page 7
					
						
				
Model-Based Loads Observer Approach for Landing Gear Remaining Useful Life Prediction
					Page 11
					
						
				
Process Quality Monitoring Through a LSTM Network Derived from a Rule-Based Approach
					Page 9
					
						
				
Threshold Selection for Classification Models in Prognostics
Doctoral Symposium
Design Of Digital Twins for In-Service Support and Maintenance
					Page 4
					
						
				
Development of a Data-driven Condition-Based Maintenance Methodology Framework for an Advanced Jet Trainer
					Page 5
					
						
				
Digital Twin Development for Feed Drive Systems Condition Monitoring and Maintenance Planning
					Page 4
					
						
				
Generating Realistic Failure Data for Predictive Maintenance: A Simulation and cGAN-based Methodology
					Page 4
					
						
				
Machinery Fault Detection using Advanced Machine Learning Techniques
					Page 4
					
						
				
Natural Language Processing for Risk, Resilience, and Reliability
					Page 4
					
						
				
Prognostics of Remaining Useful Life for Aviation Structures Considering Imperfect Repairs
Trustworthy Machine Learning Operations for Predictive Maintenance Solutions
					Page 4