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
Editors:
Chetan S. Kulkarni,
Indranil Roychoudhury
Published: 2023-10-26
Technical Research Papers
Vibration Signal Decomposition using Dilated CNN
Eli Gildish, Michael Grebshtein, Yehudit Aperstein, Igor Makienko
A Grey-box Approach for the Prognostic and Health Management of Lithium-Ion Batteries
Francesco Cancelliere, Sylvain Girard, Jean-Marc Bourinet, Matteo Broggi
A NanoDet Model with Adaptively Weighted Loss for Real-time Railroad Inspection
Jiawei Guo, Sen Zhang, Yu Qian, Yi Wang
A Hybrid Model-Based and Data-Driven Framework for Automated Spacecraft Fault Detection
Eric Pesola, Ksenia Kolcio, Maurice Prather, Adrian Ildefonso
A State Machine-Based Approach for Estimating the Capacity Loss of Lithium-Ion Batteries
Ruth David, Dirk Söffker
A Case Study Comparing ROC and PRC Curves for Imbalanced Data
Dan Watson, Dr. Karl Reichard, Aaron Isaacson
A Sequential Hybrid Method for Full Lifetime Remaining Useful Life Prediction of Bearings in Rotating Machinery
koengeurts, Kerem Eryilmaz, Ted Oijevaar
Adaptive Prognostics: A reliable RUL approach
Nick Eleftheroglou
An Energy Consumption Auditing Anomaly Detection System of Robotic Manipulators based on a Generative Adversarial Network
Ge Song, Seong Hyeon Hong, Tristan Kyzer, Yi Wang
Battery State-of-Health Aware Path Planning for a Mars Rover
Mariana Salinas-Camus, Chetan Kulkarni, Marcos Orchard
Context-aware machine learning for estimating the remaining useful life of bearings under varying speed operating conditions
Ali Hosseinli, Ted Ooijevaar, Konstantinos Gryllias
Co-design Model for Neuromorphic Technology Development in Rolling Element Bearing Condition Monitoring
Daniel Strombergsson, Ashwani Kumar, Fredrik Sandin, Pär Marklund
DAGGER: Data AuGmentation GEneRative Framework for Time-Series Data in Data-Driven Smart Manufacturing Systems
Nicholas Hemleben, Daniel Ospina-Acero, David Blank, Andrew VanFossen, Frank Zahiri, Mrinal Kumar
Data Augmentation of Sensor Time Series using Time-varying Autoregressive Processes
Douglas Baptista de Souza, Bruno Paes Leao
Data-Driven Approaches to Diagnostics and State of Health Monitoring of Maritime Battery Systems
Erik Vanem, Qin Liang, Carla Ferreira, Christian Agrell, Nikita Karandikar, Shuai Wang, Maximilian Bruch, Clara Bertinelli Salucci, Christian Grindheim, Anna Kejvalova, Øystein Alnes, Kristian Thorbjørnsen, Azzeddine Bakdi, Rambabu Kandepu
A Comparison of Residual-based Methods on Fault Detection
Chi-Ching Hsu, Gaetan Frusque, Olga Fink
Design and Implementation of a Model Selection Pipeline for Prognostics and Health Management in the Operational Environment
Peter Bishay, Lukens Sarah, Rousis Damon, Danneman Nathan
Diagnostic Signal Method for Fault Identification of Electro-Hydraulic Servo Actuators
Zihan Liu, Prashant Kambali, Chandrashekhar Nataraj
Differentiable Short-Time Fourier Transform Window Length Selection Driven by Cyclo-Stationarity
Douw Marx, Konstantinos Gryllias
Ensemble Learning Based Convolutional Neural Networks for Remaining Useful Life Prediction of Aircraft Engines
Thambirajah Ravichandran, Bolun Cui, Sri Namachchivaya, Amar Kumar, Alka Srivatsava, Yuan Liu
Explainable Predictive Maintenance is Not Enough: Quantifying Trust in Remaining Useful Life Estimation
Ripan Kumar Kundu, Khaza Anuarul Hoque
Explainable Prognostics Method through Differential Evolved RVR Ensemble of Relevance Vector Machines
Miltiadis Alamaniotis
Exploring Filter Banks and Spike Interval Statistics of Level-Crossing ADCs for Fault Diagnosis of Rolling Element Bearings
Ashwani Kumar, Daniel Strömbergsson, Par Marklund, Fredrik Sandin
Few-shot Learning for Plastic Bearing Fault Diagnosis – An Integrated Image Processing and NLP Approach
David He, Miao
Graph neural networks for dynamic modeling of roller bearings
Vinay Sharma, Jens Ravesloot, Cees Taal, Olga Fink
Fault Severity Estimation in Cracked Shafts by Integration of Phase Space Topology and Convolutional Neural Network
Utkarsh Andharikar, Amirhassan Abbasi, Prashant Kambali, C. Nataraj
Increasing Robustness of Data-Driven Fault Diagnostics with Knowledge Graphs
Maximilian-Peter Radtke, Marco Huber, Jürgen Bock
Limitations and Opportunities in PHM for Offshore Wind Farms: A Socio-Technical-Ecological System Perspective
Arvind Keprate
Labelling of Annotated Condition Monitoring Data Through Technical Language Processing
Karl Lowenmark, Cees Taal, Amit Vurgaft, Joakim Nivre, Marcus Liwicki, Fredrik Sandin
Operational Wheel Flat Detector in Railway Vehicles
Ibon Erdozain, Blas Blanco, Luis Baeza, Asier Alonso
Parameters identification of the satellite attitude control system with large inertia rotating components
Xueqin Chen, Boyu Yang, Fan Wu, Hongxu Wang, Qihan Ma, Chengfei Yue
Prognosis of Li-ion Batteries Under Large Load Variations Using Hybrid Physics-Informed Neural Networks
Kajetan Fricke, Renato Nascimento, Matteo Corbetta, Chetan Kulkarni, Felipe Viana
Promoting Explainability in Data-Driven Models for Anomaly Detection: A Step Toward Diagnosis
Quentin Dollon, Paul Labbé, François Léonard
Reconceptualizing the Prognostics Digital Twin for Smart Manufacturing with Data-Driven Evolutionary Models and Adaptive Uncertainty Quantification
Jack Murray, Brandon Chamberlain, Nicholas Hemleben, Daniel Ospina-Acero, Indranil Nayak, Andrew VanFossen, Frank Zahiri, Mrinal Kumar
Rethinking Reliability in Terms of Margins
Diego Mandelli, Congjian Wang, Koushik Manjunatha, Vivek Agarwal, Linyu Lin
Sensitivity enhanced method for fault detection and prediction of elevator doors using a margin maximized hyperspace
Minjae Kim, Seho Son, Kiyong Oh
Unsupervised Physics-Informed Health Indicator Estimation for Complex Systems
Kristupas Bajarunas, Marcia Baptista, Kai Goebel, Manuel Arias Chao
Underlying Probability Measure Approximated by Monte Carlo Simulations in Event Prognostics
David Acuña-Ureta, Marcos Orchard
Industry Experience Papers
A Closer Look at Bearing Fault Classification Approaches
Harika Abburi, Tanya Chaudhary, Sardar Haider Waseem Ilyas, Lakshmi Manne, Deepak Mittal, Don Williams, Derek Snaidauf, Edward Bowen, Balaji Veeramani
A Framework for Rapid Prototyping of PHM Analytics for Complex Systems using a Supervised Data-Driven Approach
Katarina Vuckovic, Shashvat Prakash, Ben Burke
A Hypothesis testing approach to Zero-Fault-Shot learning for Damage Component Classification
Eric Bechhoefer, Omri Matania, Jacob Bortman
A Novel Operations-Based Application of Natural Language Processing to Enhance Aircraft System Troubleshooting
Jamie Asbach, Daniel Wade
Automotive Electronic Control Unit Ground Line Health Monitoring Method
Alaeddin Milhim, Hadyan Ramadhan, Xinyu Du, Shengbing Jiang, Hossein Sadjadi
Deep Regression Network with Prediction Confidence in Time Series Application for Asset Health Estimation
Hao Huang, Arun Subramanian, Abhinav Saxena, Nurali Virani, Naresh Iyer
Evaluating the Performance of ChatGPT in the Automation of Maintenance Recommendations for Prognostics and Health Management
Sarah Lukens, Asma Ali
Enhancing Realistic Remaining Useful Life Prediction using Multi-Fidelity Physic-Informed Neural Network Approach
Yoojeong Noh, Solichin Mochammad, Nam Ho Kim
Fault Detection and Diagnosis in Tennessee Eastman Process with Deep Autoencoder
Zhongying Xiao, Arthur Kordon, Subrata Sen
Identifying Key Factors in Turbofan Engine Health Degradation using Functional Analysis
Declan Mallamo, Michael Azarian, Michael Pecht
Joint feedback control and fault diagnosis disambiguation
Ion Matei, Maksym Zhenirovsky, Johan de Kleer, Kai Goebel
OSPtk: Cost-aware Optimal Sensor Placement Toolkit Enabling Design-for-PHM in Critical Industrial Systems
Liang Tang, Abhinav Saxena, Scott Evans, Naresh Iyer, Helena Goldfarb
Process for Turboshaft Engine Performance Trending
Eric Bechhoefer, Mina Hajimohammadali
Predictive Analytics for Hydropower Fleet Intelligence
Yigit Yucesan, Pradeep Ramuhalli, Yang Chen, Jim Miller, Edward Hanson, Stephen Signore
Servomotor Dataset: Modeling Health in Mechanisms with Typically Intermittent Operation
Arun Subramanian, Abhinav Saxena, Jamie Coble
Signal pre-processing techniques for fault signature enhancement in a bearing health monitoring system used in the automotive industry
Ehsan Jafarzadeh, Sara Rahimifard, Paola Sant Anna, Yu Cao, Frances Tenney, Hossein Sadjadi
Unsupervised Causal Deep Learning-Based Anomaly Detection in Nuclear Power Plant Applications
Abhinav Saxena, Helena Goldfarb, Jeffrey Clark
Doctoral Symposium Summaries
A Physics-informed, Transfer Learning Approach to Structural Health Monitoring
Trent Furlong, Karl Reichard
A Neural Network Framework for Predicting Durability and Damage Tolerance of Polymer Composites under Combined Hygrothermal-mechanical Loading
Partha Pratim Das
Generic Hybrid Models for Prognostics of Complex Systems
Kristupas Bajarunas
Integrating Advanced Prognostic Methods for Accurate Remaining Useful Life Prediction in Industrial Systems
Hyung Jun Park, Nam Ho Kim, Joo-Ho Choi
Information Fusion and Data Augmentation for Risk-based Maintenance Optimization of Hydrogen Gas Pipelines
Kaushik Kethamukkala, Yongming Liu
Mission-Specific Prognosis of Li-ion Batteries using Hybrid Physics-Informed Neural Networks
kajetanfricke
Physics-Informed Deep Learning-Based Approach for Probabilistic Modeling of Degradation
Hamidreza Habibollahi Najaf Abadi
Vehicle State Monitoring and Fault Detection System for Unmanned Ground Vehicles (UGV) using Markov Models
Kalpit Vadnerkar, Pierluigi Pisu
Poster Presentations
A Fine-grained Semi-supervised Anomaly Detection Framework for Predictive Maintenance of Industrial Assets
Xiaorui Tong, Wee Quan Jung, Jeremy Frimpong Banning
Accelerated Degradation Test on Electric Scroll Compressor Using Controlled Continuous Liquid Slugging
Hadyan Ramadhan, Hong Wong, Alaeddin Bani Milhim, Hossein Sadjadi
An Introductory Approach to Time-Series Data Preparation and Analysis
Edward Baumann, Charles Hsu, Hayley Buba, Taylor Cox
Cooling Fan Failure Modes to Enable Development of Automotive ECU Fan Health Monitoring System
Alaeddin Banimilhim, Jacqueline Del Gatto, Hossein Sadjadi
Failure Mode Investigation to Enable LiDAR Health Monitoring for Automotive Application
Fred Chang, Ehsan Jafarzadeh, Jacqueline Del Gatto, Graham Cran, Hossein Sadjadi
Fusion and Comparison of Prognostic Models for Remaining Useful Life of Aircraft systems
Shuai Fu, Nicolas P. Avdelidis, Angelos Plastropoulos, Ip-Shing Fan
Interpolate and Extrapolate Machine Learning Models using An Unsupervised Method
Peng Liu
System-based Monitoring of Muscular Fatigue in Lower-Extremity Movement
Samuel Bertelson, Lindsey Molina, Richard Neptune, Dragan Djurdjanovic
Using Charge Determination Design of Experiments to Develop A Refrigerant Charge Health Status Model for Heat Pump Systems
Hong Wong, Hadyan Ramadhan, Alaeddin Bani Milhim, Hossein Sadjadi
Data Challenge Papers
An Introduction to 2023 PHM Data Challenge: The Elephant in the Room and an Analysis of Competition Results
Yongzhi Qu, Jesse William, Abhinav Saxena, Neil Eklund, Scott Clements
Anomaly Detection and Fault Classification in Multivariate Time Series Using Multimodal Deep Models
Gunwoo Ryu, Nohyoon Seong
Gearbox Degradation Prediction through Deep CNN and Bayesian Optimization
Kai Shen
Gear Pitting Fault Diagnosis Using Domain Generalizations and Specialization Techniques
Fan Chu
Predicting pitting severity in gearboxes under unseen operating conditions and fault severities using convolutional neural networks with power spectral density inputs
Rik Vaerenberg, Douw Marx, Seyed Ali Hosseinli, Fabrizio De Fabritiis, Hao Wen, Rui Zhu, Konstantinos Gryllias