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 2022 Management Team, Publisher Information and Table of Contents
Technical Papers
Experiences of a Digital Twin Based Predictive Maintenance Solution for Belt Conveyor Systems
Page 1-8
A Case-study Led Investigation of Explainable AI (XAI) to Support Deployment of Prognostics in the industry
Page 9-20
Long Horizon Anomaly Prediction in Multivariate Time Series with Causal Autoencoders
Page 21-31
Experimental Validation of Multi-fidelity Models for Prognostics of Electromechanical Actuators
Page 32-42
An Analysis of Vibrations and Currents for Broken Rotor Bar Detection in Three-phase Induction Motors
Page 43-48
Online Flow Estimation for Condition Monitoring of Pumps in Aircraft Hydraulics
Page 49-57
Hybrid Fault Prognostics for Nuclear Applications: Addressing Rotating Plant Model Uncertainty
Page 58-67
Data-driven Prognostics based on Evolving Fuzzy Degradation Models for Power Semiconductor Devices
Page 68-77
State of Health and Lifetime Prediction of Lithium-ion Batteries Using Self-learning Incremental Models
Page 78-86
Wrong Injection Detection in a Small Diesel Engine, a Machine Learning Approach
Page 87-95
Novel Metrics to Evaluate Probabilistic Remaining Useful Life Prognostics with Applications to Turbofan Engines
Page 96-109
Filtering Misleading Repair Log Labels to Improve Predictive Maintenance Models
Page 110-117
Physics-informed Lightweight Temporal Convolution Networks for Fault Prognostics Associated to Bearing Stiffness Degradation
Page 118-125
Design and validation of scalable PHM solutions for aerospace onboard systems
Page 126-135
Sensor Fault/Failure Correction and Missing Sensor Replacement for Enhanced Real-time Gas Turbine Diagnostics
Page 136-145
Helicopter Bolt Loosening Monitoring using Vibrations and Machine Learning
Page 146-155
On the Integration of Fundamental Knowledge about Degradation Processes into Data-Driven Diagnostics and Prognostics Using Theory-Guided Data Science
Page 156-165
Toward Runtime Assurance of Complex Systems with AI Components
Page 166-174
Machine Learning Methods for Health-Index Prediction in Coating Chambers
Page 175-181
Approximate Bayesian Computation as a New Tool for Partial Discharge Analysis of Partial Discharge Data
Page 182-192
Unsupervised Prognostics based on Deep Virtual Health Index Prediction
Page 193-199
Autoencoder Based Anomaly Detection and Explained Fault Localization in Industrial Cooling Systems
Page 200-210
Joint Autoencoder-Classifier Model for Malfunction Identification and Classification on Marine Diesel Engine Diagnostics Data
Page 211-218
Physics Informed Neural Network for Health Monitoring of an Air Preheater
Page 219-230
A Health Index Framework for Condition Monitoring and Health Prediction
Page 231-238
Tool Compatibility Index: Indicator Enables Improved Tool Selection for Well Construction
Page 239-244
An End-to-End Pipeline for Uncertainty Quantification and Remaining Useful Life Estimation: An Application on Aircraft Engines
Page 245-260
Fault Detection in a Wind Turbine Hydraulic Pitch System Using Deep Autoencoder Extracted Features
Page 261-268
iVRIDA: intelligent Vehicle Running Instability Detection Algorithm for High-speed Rail Vehicles using Temporal Convolution Network – A Pilot Study
Page 269-277
Remaining-Useful-Life prognostics for opportunistic grouping of maintenance of landing gear brakes for a fleet of aircraft
Page 278-285
Novel Graph-Based Features for Bearing Fault Diagnosis: Two Aspects of Time Series Structure
Page 286-293
Certainty Groups: A Practical Approach to Distinguish Confidence Levels in Neural Networks
Page 294-305
Processing of Condition Monitoring Annotations with BERT and Technical Language Substitution: A Case Study
Page 306-314
A Design Methodology for Robust Model-Based Fault Diagnosis Schemes and its Application to an Aircraft Hydraulic Power Package
Page 315-328
Prognosis of Wear Progression in Electrical Brakes for Aeronautical Applications
Page 329-337
Domain Knowledge Informed Unsupervised Fault Detection for Rolling Element Bearings
Page 338-350
Estimation of Wind Turbine Performance Degradation with Deep Neural Networks
Page 351-359
Weighted-QMIX-based Optimization for Maintenance Decision-making of Multi-component Systems
Page 360-367
Data Driven Seal Wear Classifications using Acoustic Emissions and Artificial Neural Networks
Page 368-375
Severity Estimation of Faulty Bearings Based on Strain Signals From Physical Models and FBG Measurements
Page 376-383
A Comparative Study of Health Monitoring Sensors based on Prognostic Performance
Page 384-391
Forecasting Piston Rod Seal Failure Based on Acoustic Emission Features in ARIMA Model
Page 3392-400
Improved Time-Frequency Representation for Non-stationary Vibrations of Slow Rotating Machinery
Page 401-409
Towards Data Reliability Based on Triple Redundancy and Online Outlier Detection
Page 410-420
Expert Knowledge Induced Logic Tensor Networks: A Bearing Fault Diagnosis Case Study
Page 421-431
Domain Adaptation in Predicting Turbocharger Failures Using Vehicle’s Sensor Measurements
Page 432-439
Experimental Assessment of a Broadband Vibration and Acoustic Emission Sensor for Rotorcraft Transmission Monitoring
Page 440-448
Optical Cutting Tool Wear Monitoring by 3D Geometry Reconstruction
Page 449-457
Data-Driven Fault Detection for Transmitter in Logging-While-Drilling Tool
Page 458-465
Autonomous Bearing Tone Tracking Algorithm
Page 466-472
Noise-Robust Representation for Fault Identification with Limited Data via Data Augmentation
Page 473-479
Automating Critical Surface Identification and Damage Detection Using Deep Learning and Perspective Projection Methods
Page 480-489
State of Health Forecasting of Heterogeneous Lithium-ion Battery Types and Operation Enabled by Transfer Learning
Page 490-508
Failures Mapping for Aircraft Electrical Actuation System Health Management
Page 509-520
An Approach to Condition Monitoring of BLDC Motors with Experimentally Validated Simulation Data
Page 521-529
Uncertainty Informed Anomaly Scores with Deep Learning: Robust Fault Detection with Limited Data
Page 530-540
Doctoral Symposium
Deep Learning Representation Pre-training for Industry 4.0
Page 571-573
Physics Informed Self Supervised Learning For Fault Diagnostics and Prognostics in the Context of Sparse and Noisy Data
Page 574-576
A Novel Way to Apply Transfer Learning to Aircraft System Fault Diagnosis
Page 577-579
The Application, Utility and Acceptability of Data Analytics in Safety Risk Management of Airline Operations
Page 580-582
Diagnosis and Fault-Tolerant Control for a Multi-Engine Cluster of a Reusable Launcher with Sensor and Actuator Faults
Page 583-585
Artificial-Intelligence-Based Maintenance Scheduling for Complex Systems with Multiple Dependencies
Page 586-589
Contribution to the Design and Implementation of a Reflexive Cyber-Physical System: Application to Air Quality Prediction in the Vallees des Gaves
Page 590-593
Combining Knowledge and Deep Learning for Prognostics and Health Management
Page 594-597
Data Challenge Winners
A Hierarchical XGBoost Early Detection Method for Quality and Productivity Improvement of Electronics Manufacturing Systems
Page 541-549
Application of Machine Learning Methods to Predict the Quality of Electric Circuit Boards of a Production Line
Page 550-555
A Novel Methodology for Health Assessment in Printed Circuit Boards
Page 556-562
Prediction of Production Line Status for Printed Circuit Boards
Page 563-570