About the Journal

The annual Conference of the Prognostics and Health Management (PHM) Society is held each autum in North America 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
Technical Papers
A Data Management Framework & UAV Simulation Testbed for the Study of System-level Prognostics Technologies
Timothy Darrah, Jeremy Frank, Marcos Quinones-Grueiro, Gautam Biswas
A Particle-Swarm-Optimization-Based Approach for the State-of-Charge Estimation of an Electric Vehicle When Driven Under Real Conditions
Aramis Perez, Francisco Jaramillo, Cesar Baeza, Martin Valderrama, Vanessa Quintero, Marcos Orchard
A Study of Deep Neural Networks Transfer Learning For Fault Diagnosis Applications
Michael Franco-Garcia, Nithya Nalluri, Alex Benasutti, Larry Pearlstein, Mohammed Alabsi
Active Learning Framework for Time-Series Classification of Vibration and Industrial Process Data
Sergio Martin del Campo Barraza, William Lindskog, Davide Badalotti, Oskar Liew, Arash Toyser
Aligning the Production Planning and Control Process with Prognostics and Health Management
Kevin Wesendrup, Bernd Hellingrath
An Application Based Comparison of Statistical Versus Deep Learning Approaches to Reciprocating Compressor Valve Condition Monitoring
Jacob Chesnes, Jason Kolodziej
An End-to-End Learning Framework for Early Prediction of Battery Capacity Trajectory
Jinqiang Liu, Adam Thelen, Chao Hu, Xiao-Guang Yang
An Offline Deep Reinforcement Learning for Maintenance Decision-Making
Hamed Khorasgani, Haiyan Wang, Chetan Gupta, Ahmed Farahat
Analysis of the Deployment Strategies of Reinforcement Learning Controllers for Complex Dynamic Systems
Ibrahim Ahmed, Marcos Quinones Grueiro, Gautam Biswas
Autoencoder Based Anomaly Detector for Gear Tooth Bending Fatigue Cracks
Adrian Hood, Christopher Valant, Patrick Horney, Allen Jones, Jared S. Lantner, Josiah Martuscello, Nenad Nenadic
Bayesian Network Based Causal Map Generation and Root Cause Identification in Complex Industrial Processes
Kalyani Zope, Tanmaya Singhal, Sri Harsha Nistala, Venkataramana Runkana
Brinell Fault Injection to Enable Development of a Wheel Bearing Fault Monitoring System for Automobiles
Graeme Garner, Samba Drame, Xinyu Du, Hossein Sadjadi
Collaborative Prognostics for Machine Fleets Using a Novel Federated Baseline Learner
Vibhor Pandhare, Xiaodong Jia, Jay Lee
Condition Monitoring of Wind Turbines and Extraction of Healthy Training Data using an Ensemble of Advanced Statistical Anomaly Detection Models
Xavier Chesterman, Timothy Verstraeten, Pieter-Jan Daems, Ann Nowé, Jan Helsen
Data-Driven Diagnostics and Prognostics for Modelling the State of Health of Maritime Battery Systems – a Review
Erik Vanem, Øystein Åsheim Alnes, James Lam
Deep Unsupervised Transfer Learning for Health Status Prediction of a Fleet of Wind Turbines with Unbalanced Data
Dandan Peng, Chenyu Liu, Wim Desmet, Konstantinos Gryllias
Degradation Detection for Internal Gear Pumps using Pressure Reduction Time Maps
Kurt Pichler, Rainer Haas, Veronika Putz, Christian Kastl
Diagnosing Systems through Approximated Information
Alexander Diedrich, Oliver Niggemann
Digital Twin-Driven Process and Equipment FMECA Generation for Smart Manufacturing Applications
Sudipto Ghoshal, Jay Meyer, Venkat Malepati, Caleb Hudson, Somnath Deb, Andrew Hess, Feraidoon Zahiri, Gregory Sutton
Electric Power Steering Power Circuit Health Assessment and Mitigation Strategy
Wen-Chiao Lin, Graeme Garner, Yat-Chung Tang, Arash Mohtat
Enhancing the Diagnostic Performance of Condition Based Maintenance Through the Fusion of Sensor with Maintenance Data
Henrik Simon, Sascha Schoenhof
Estimating Dynamic Cutting Forces of Machine Tools from Measured Vibrations using Sparse Regression with Nonlinear Function Basis
Yongzhi Qu, Gregory W. Vogl
Evaluating and Optimizing Analytic Signals
Shashvat Prakash, Antoni Brzoska
Explainable Machinery Faults Prediction Using Ensemble Tree Classifiers: Bagging or Boosting?
Somayeh Bakkhtiari Ramezani, Amin Amirlatifi, Thomas Kirby, Maria Seale, Shahram Rahimi
Exploring Cloud Assisted Tiny Machine Learning Application Patterns for PHM Scenarios
Xingyu Zhou, Zhuangwei Kang, Robert Canady, Shunxing Bao, Daniel Allen Balasubramanian, Aniruddha Gokhale
Fault Detection in a Physcially Redundant MEMS Accelerometer Array
Daniel Watson, Karl Reichard
Fault Detection via Sparsity-based Blind Filtering on Experimental Vibration Signals
Kayacan Kestel, Cédric Peeters, Jérôme Antoni, Jan Helsen
Health Indicators to Estimate Health of Magnetic Wheel Encoder
Jasmeet Singh Ladoiye, Douglas Spry, Milad Jalali
Interpretation of Deep Learning Models in Bearing Fault Diagnosis
Menno Liefstingh, Cees Taal, Sebastián Echeverri Restrepo, Alireza Azarfar
Learning an Optimal Operational Strategy for Service Life Extension of Gear Wheels with Double Deep Q Networks
Mark Henss, Yvonne Gretzinger, Tamer Tevetoglu, Maximilian Posner, Bernd Bertsche
Li-ion Battery Aging with Hybrid Physics-Informed Neural Networks and Fleet-wide Data
Renato G. Nascimento, Matteo Corbetta, Chetan S. Kulkarni, Felipe A. C. Viana
Methodology on Establishing Multivariate Failure Thresholds for Improved Remaining Useful Life Prediction in PHM
Wenzhe Li, Xiaodong Jia, Yuan-Ming Hsu, Youwen Liu, Jay Lee
Methods to Improve the Prognostics of Time-to-Failure Models
Edward Baumann, Pedro A. Forero, Gray Selby, Charles Hsu
Modeling Health Status Identification in a Gas Turbine System: Three-Class Classification Approaches
Catherine Cheung, Calista Biondic, Zouhair Hamaimou, Julio J. Valdes
Modeling the Business Value of a Predictive Maintenance System using Monte Carlo Simulation
Graeme Garner, Paola Santanna, Hossein Sadjadi
Model-based Damage Detection through Physics Guided Learning
Ali I. Ozdagli, Xenofon Koutsoukos
On Adversarial Vulnerability of PHM algorithms – An initial Study
Weizhong Yan, Zhaoyuan Yang, Jianwei Qiu
Prognostics and Secure Health Management of Electronic Systems in a Zero-Trust Environment
Varun Khemani, Michael H. Azarian, Michael G. Pecht
Remaining Useful Life Calculation of a Component using Hybrid Fatigue Crack Model
Eric Bechhoefer, Lei Xiao, Xinghui Zhang
Remaining Useful Life Estimation using Event Data
Mahbubul Alam, Laleh Jalali, Dipanjan Ghosh, Ahmed Farahat, Chetan Gupta
Safety Diagnostics and Degraded Operational Modes for Off-road Unmanned Ground Combat Vehicles
Naveen Aditya Verma Dantuluri, Pierluigi Pisu
Suspension Fault Diagnostics Using Vehicle Pitch and Roll Models
XinyuDu, Lichao Mai, Hossein Sadjadi
Data Challenge Winners
Remaining Useful Life Prediction of Aircraft Engines with Variable Length Input Sequences
Andreas Lövberg
Inception Based Deep Convolutional Neural Network for Remaining Useful Life Estimation of Turbofan Engines
Nathaniel DeVol, Christopher Saldana, Katherine Fu
A Stacked Deep Convolutional Neural Network to Predict the Remaining Useful Life of a Turbofan Engine
David Solís-Martín, Juan Galán-Páez, Joaquín Borrego-Díaz
Poster Presentations
Building an Air Turbine Conditional Anomaly Detection Approach for Wave Power Plants
Jose Ignacio Aizpurua, Markel Penalba, Natalia Kirillova, Illart Alcorta, Jon Lekube, Dorleta Marina
Enhanced Visualization of Production Systems Concepts and Simulation Data for the Smart/Digital Factory
James Ong, Anand Paul, Daniel Tuohy, Feraidoon Zahiri, Gregory Sutton
Strategies to Improve Robustness of a Health Monitoring System, with Application to Brake Rotors
Hamed Kazemi, Graeme Garner, Samba Drame, Xinyu Du, Hossein Sadjadi