About the Journal
The Asia-Pacific Conference of the Prognostics and Health Management (PHM) Society is held in the spring of odd years (starting in 2017) 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
Published: 2026-01-13
Plenary Papers
PHM-Vibench
Qi Li, Bojian Chen, Xuan Li, Qitong Chen, Liang Chen, Changqing Shen, Lu Lu, Zhaoye Qin, Fulei Chu
Data Challenge Papers
A Feature-Engineering-Based Machine Learning Approach for Cutter Flank Wear Prediction under Data-Scarce Conditions
Paula Mielgo, Marcos Quinones-Grueiro, Anibal Bregon, Austin Coursey, Carlos J. Alonso-González, Gautam Biswas
Regular Session Papers
A Bidirectional Structure Constraint framework for Domain Generalization in Intelligent Fault Diagnosis
Wenjing Zhou, Liang Chen, Hong Zhuang, Qitong Chen
A CNN-Multi-Head Attention Framework for Gearbox Incremental Fault Diagnosis Under Non-Stationary Conditions
Hao Zhang, Shunuan Liu, Bin Luo, Konstantinos Gryllias, Chenyu Liu
A Lightweight Neural Network for End-to-End Bearing Fault Diagnosis in Multi-Sensor Scenarios
Yichao Li, Yanfang Liu, Xiangyang Xu
A Multi-Sensor Fault Diagnosis Method for Aero-Engine Bearings Based on Complex-Valued Convolution and Dual Attention Mechanism
Shuquan Xiao, Xueyi Li, Tianyang Wang, Fulei Chu
A Practical Hybrid Framework for RUL Prediction in Ion Mill Etching by Integrating Operational States
minamitu
A Prediction of Thermal Stress Profiles in the Steam Turbine Startup Phase Using Fourier Neural Operator
LEE SoJung
A System of Systems Architecture for Optimizing Aircraft Health Management in Civil Aviation
Takuro Koizumi, Nozomu Kogiso
A Transfer Learning Framework for Remaining Useful Life Estimation
Melanie Bianca Sigl, Klaus Meyer-Wegener
Adversarial Domain Adaptation Fault Diagnosis Method Based on Self-attention Graph Convolutional Network
Bo Zhang, shuai su, Ning Ma, Yingxue Wang, Wei Li
AI-Driven Design Optimization of Engineering Systems: A Case Study on Turboshaft Engines
Satish Thokala, Peeyush
AI-Powered Runway Safety: YOLOv11-Based Detection of Foreign Object Debris
Phani Kiran Yellakara, Srinivasarao Surapu
An Innovative Machine Learning driven approach to detect anomalous behavior of Dry Gas Seal Heaters for Centrifugal Compressors
Meenali Sharma, Carmine, Laura Nuti, Unnat Mankad, Gabriele Mordacci, Rajakumar D, Aidil Fazlina Hasbullah
Anomaly Detection Framework for Rotary Equipment Using ContinuousWavelet Transform and U-Net Autoencoders
Mohamed Zamil Kanjirathingal Rafeek, Ulrich Schäfer
Assessment of simulation-based data augmentation technique by Uncertainty Quantification for Spacecraft Propulsion System PHM
Shotaro Hamato, Himeko Yamamoto, Noriyasu Omata, Yu Daimon, Seiji Tsutsumi
Bivariate degradation modeling and reliability analysis based on a shared frailty factor with truncated normal distribution
Lu Li, Zhihua Wang
Causal Graph-Based Anomaly Detection for Battery Modules in Electric Heavy-Duty Vehicles
Yuantao Fan, Carlos Camacho, Sepideh Pashami, Slawomir Nowaczyk
Cleaning Maintenance Logs with LLM Agents for Improved Predictive Maintenance
Valeriu Ionut Dimidov, Faisal Hawlader, Sasan Jafarnejad, Raphael Frank
Combining Statistical Models and AI for Predictive Maintenance: RUL Estimation of Reactor Protection System Components
Jung Hwan Kim, Chang Hwoi Kim, Joon Ha Jung, Sangchul Park
A Hybrid Semi-Supervised Framework for Full Life-Cycle Degradation Trajectory Learning and RUL Estimation
Xianpeng Qiao, Veronica Lestari Jauw, Tiyamike Bnada, Chin Seong Lim
Damage Localization in a CFRP Beam via Modal Frequency Shifts and Nearest Neighbor Classification
Ömer Dehan Özboz, Özkan Altay, Murat Özbayoğlu, Özgür Ünver
Data-driven Anomaly Detection for Quadcopter UAV Indoor Flight Platform
Gengyu Li, Chun Fui Liew, Naoya Takeishi, Takehisa Yairi
Development and Sharing of a Multi-Modal Indoor UAV Dataset for PHM Research
Chun Fui Liew, Gengyu Li, Akira Osaka, Samir Khan, Naoya Takeishi, Takehisa Yairi
Development of a Hierarchical Anomaly Detection System for Steelmaking Processes and Proposal of a Model Update Method
Yohei Harada, Masafumi Matsushita, Takehide Hirata
Development of a HUMS for UAV hybrid power system using digital twin and AI techniques
Chiara Sperlì
Development of an Interactive Twinverse System
Yongho Lee, Huichan Park, Seongbin Choi, Sang Won Lee
Development of Bearing Fault Diagnosis Model Using Low Frequency Data Based on Knowledge Distillation
Yongjae Jeon, Secheol Yang, Sang Won Lee
Development of Virtual Thermal Sensor based on Multivariate Time Series Prediction for Estimating Internal Contact Temperature of High-Voltage Relays
Sewoong Gim, Jaephil Park, Sanghoon Lee
Enabling Condition Based Maintenance Strategy for Radar Systems – Data Driven Approach
Rafik HADJRIA
Enabling Model-Based RAMS Through LLM-Driven Legacy Data Transformation
You-Jung Jun, Navid T. Zaman, Derek Kim, Stecki Yanek, Raphaël Chagnoleau
Enhanced Fault Isolation and Part Recommendation for Airplane Health Management with Hybrid Probabilistic Modeling
Partha Adhikari, Seema Chopra, Darren Macer, Surya Pratap Singh Yadav, Sivakumar Thiyagarajan
Enhancing Machine Reliability in Industrial Plants Leveraging Diagnostic and Prognostic Approach to measure reliability improvements
Pranay Mathur, Carlo Michelassi, Leonardo Vieri, Gilda Pedoto
Evaluating Failure Time Probabilities for Compound Degradation with Linear Path and Mixed Jumps
Shihao Cao, Zhihua Wang, Xiangmin Ouyang, Pengjun Zeng
Explainable and Trustworthy AI for Fault Classification in the Tennessee Eastman Process: A Step Toward Industrial Autonomy
Jayanth Balaji Avanashilingam, Bijuraj Pandiyath Velayudhan
Fault-Induced Signal Distortion in FMCW Automotive Radar: A Simulation-Based Analysis
Sheriff Murtala, Ingyu Lee, Soojung Hur, Gyusang Choi
Flare Gas Flow Rate Estimation Using Multimodal Deep Learning
Yu Watanabe, Kento Ishii, Nana Tamai, Takehisa Yairi, Naoya Takeishi
Fractal-based Satellite Health Monitoring
Lucio Pinello, Lorenzo Brancato, Alessandro Lucchetti, Francesco Cadini, Marco Giglio
From Engineering Drawings to Assembly Instructions: A Vision and Language Model Approach
Shokhikha Amalana Murdivien, Minji Kim, Kyung Wan Choi, Jumyung Um
From state observer to deep neural network: design, optimization, and application in bearing dynamics modeling
Yiliang Qian, Yan Wang, Diwang Ruan, Zhaorong Li, Jianping Yan, Clemens Gühmann
Graph-Based Adaptive Anomaly Detection Framework for Dual-Fuel Marine Engines
Jaewoong Choi, Yoojeong Noh, Young-Jin Kang
Hierarchical Anomaly Detection and Model Update Framework for Steel Manufacturing
Yohei Harada, Masafumi Matsushita, Takehide Hirata
Improved LSTM-Based Battery SOH Estimation with Differential Evolution Hyperparameter Optimization
Karthickumar Ponnambalam, Sivaneasan Bala Krishnan, Anurag Sharma, Sze Sing Lee
Improving Virtual Metrology Predictions via Transfer Learning and Active Learning
Swee Kuan Loh
Intelligent Bearing Fault Diagnosis Under Various Load Conditions Using Bias Mitigation
Seungyun Lee, Sungjong Kim, Minjae Kim, Heonjun Yoon, Byeng D. Youn
Interpretable Sensor Importance-Based Multi-Sensor Integration for Condition Monitoring of Rotating Machinery
Sungjong Kim, Seungyun Lee, Minjae Kim, Heonjun Yoon, Byeng D. Youn
Irregular Time-Series Hybrid Model for Enhanced Prognostics of Engine Degradation and Failures
Rohit Deo, Aman Yadav, Shruti Bharti, Dr. Nilesh Powar
Leveraging Few-Shot In-Context Learning for Scaling Railway Log Anomaly Detection
Quentin Possamaï, Rajesh Bonangi, Alexandre Trilla, Ossee Josepha Charlesia Yiboe, Kenza Saiah, Nenad Mijatovic
LLM-based multi-agent system for autonomous maintenance process of machine tools
Jongsu Park, Seongwoo Cho, Yoonji Chae, Sena Nur Durgunlu, Jumyung Um
Methods and Systems for Hybrid Digital Twin Driven Health Predictions for Aircraft Sub-systems
Partha Pratim Adhikari, Deepu Vettimittathu Mathai, Avik Sadhu, Darren Macer
MLOps Framework for Fault Diagnosis in Air Conditioners Using Field Noise
SangUk Son, Yoojeong Noh, Sunhwa Park, Jangwoo Lee
Multi-Branch Joint Time-Frequency Transformer for Domain Generalization Fault Diagnosis of Rotating Machinery
Qitong Chen, Liang Chen, Hong Zhuang, Qi Li, Wenjing Zhou
Multi-Class Gearbox Fault Diagnosis via Pre-Trained Model-based Domain Adaptation with Healthy-Only Target Data
Dai-Yan Ji, Hanqi Su, Shinya Tsuruta, Daichi Arimizu, Yuto Hachiya, Koji Wakimoto, Jay Lee
Multi-source Variable Decoupling Network for Compound Fault Diagnosis of Train Bogie
Qitao Yin, Zhibin Guo, Tiantian Wang, Jingsong Xie, Jinsong Yang
Multilevel fault diagnostics for railway applications using limited historical data
Osarenren Kennedy Aimiyekagbon, Alexander Löwen, Raphael Hanselle, Thomas Rief, Maximilian Beck, Walter Sextro
Nonlinear and Trend-Aware Industrial Time Series Anomaly Detection with Federated Learning
Zhiqing Luo, Yan Qin
ONGOING: A Human-readable, Model-enriching, Continuous Technician Knowledge Modeling Framework
Adrien Bolling, Sylvain Kubler
Physics-Informed Transformer with ODE-Guided Joint Modeling for Fault Classification and RUL Prediction in Collaborative Robots
Yingjun Shen, Kang Wang, Zhuoxin Chen, Junkai Huang, Yifan Zhu, Zhe Song
Predicting Maintenance Actions from Historical Logs using Domain-Specific LLMs
Aman Kumar, Ahmed Farahat, Chetan Gupta
Predictive Prioritization of Railway Bearings Using Acoustic Similarity of NOISY(RS1) Alarms from Wayside Monitoring Systems
leandro_rocha
Probabilistic graphical models for diagnosing defectivity patterns
Leonardo Barbini, Peter Kruizinga, Micha Lipplaa, Alvaro Piedrafita
Radar Health Monitoring Using Anomaly Detection
Jean-Marc Divanon, Thomas Lavigne, Theo Cornu, Teck Yoong Chai
RAVEN: Unsupervised Anomaly Detection in Multivariate Jet Engine Time Series using Residual Learning on Real Test Data
Nouf Almesafri, Mohamed Ragab, Zahi Mohamed, Abdulla Alseiari, Salama Almheiri
Real-time Sensor Data Streaming for deployment in Edge AI for Health Index Construction and Remaining Useful Life Prediction
Salama Almheiri, Zahi Mohamed, Mohamed Ragab, Abdulla Alseiari, Nouf Almesafri
Remote monitoring system for detection of faults in drive motors of electric vehicles
Amiya Mohanty, Nagesh
Robust Fault Diagnosis of Electric Vehicle Drivetrain Using Amplitude Adjustment Techniques
Jeongmin Oh, Dongjin Park, Youngrock Chung, Kyung-Woo Lee, Dae-Un Sung, Hyunseok Oh
Rotary Encoder-Based Health Indicators for Early Detection of Gear Pitting in Commercial Gearboxes
Toby Verwimp, Rui Zhu, Hao Wen, Achilleas Achilleos, Konstantinos Gryllias
Self-Adaptive RUL Prediction of Power Electronic Devices with Package Failure
Chao Guo, Zhonghai Lu
Shared Representation Learning for Generalizable SOH Estimation Across Multiple Battery Configurations
Shunyu Wu, Zhuomin Chen, Bingxin Lin, Haozheng Ye, Jiahui Zhou, Yanran Zhao, Dan Li, Jian Lou
Study of the degradation of rolling element bearings with artificial dents
Theo Tselonis, Valentius Wirjana, Thomas Hughes, Zhongxiao Peng
Towards Autonomous PHM: An Application to Turboshaft Engine Torque Prediction
David He, Eric Bechhoefer, Miao He
Towards Adaptive and Robust Unsupervised Anomaly Detection in Satellite Telemetry
Lorenzo Brancato, Alessandro Lucchetti, Francesco Cadini, Marco Giglio
Towards Open-Set Fault Diagnosis for Reactor Coolant Pumps under Unknown Fault Conditions
Jonghyeok Kim, Jeongmin Oh, Jueun Lee, Minseok Choi, Hyunseok Oh
Towards Systematic Reliability Assessment: A Multi-Criteria Decision Framework for Modeling Heat Pump Systems
Ahmed Qarqour
Unsupervised Modeling of Progressive Wear in Aircraft Engines for Predictive Maintenance
Abdellah Madane, Jérôme Lacaille, Hanane Azzag, Mustapha Lebbah
Unsupervised Health Indicator Construction via Deep Reinforcement Learning with Terminal-Dominant Reward
Zeqi Wei, Zhibin Zhao, Ruqiang Yan