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ORCIDICPHM 2023: Montreal, QC, Canada
- IEEE International Conference on Prognostics and Health Management, ICPHM 2023, Montreal, QC, Canada, June 5-7, 2023. IEEE 2023, ISBN 979-8-3503-4625-1
- Ailin Barzegar, Afshin Rahimi:
A Distributed Fault Detection and Estimation for Formation of Clusters of Small Satellites. 1-11 - Panagiotis Kakosimos
:
Reliable Thermal Monitoring of Electric Machines through Machine Learning. 12-19 - Ricardo Ludeke, P. Stephan Heyns:
Towards a Deep Reinforcement Learning based approach for real time decision making and resource allocation for Prognostics and Health Management applications. 20-29 - Siho Han, Jihwan Min, Jui Ma, Gyuil Hwang, Taeyeong Heo, Young Eun Kim, Sungjin Kang, Hyojun Kim, Sangjong Park, Kisuk Sung:
Deep Learning-Based Virtual Metrology in Multivariate Time Series. 30-37 - Zhonghai Lu, Rui Shi, Chao Guo, Mingrui Liu:
Age Feature Enhanced Neural Network for RUL Estimation of Power Electronic Devices. 38-47 - Nobal B. Niraula, Hai Nguyen, Jennifer Kansal, Sean Hafner, Logan Branscum, Eric Brown, Ricardo Garcia:
Discovering Depressurization Events in Service Difficulty Reports using Machine Learning. 48-52 - Kaiji Sun, Sindri Magnússon, Olof Steinert, Tony Lindgren:
Robust Contrastive Learning and Multi-shot Voting for High-dimensional Multivariate Data-driven Prognostics. 53-60 - Vincent Mendoza, Johnny Morgan, Marlene Haag:
Using Digital Twins for CBM+ and RAMS Decision Support. 61-66 - Rajesh Murthy:
Exploring the Use of PHM for Software System Security and Resilience. 67-72 - Chaoang Xiao, Jianbo Yu, Pu Yang, Shang Yue, Ruixu Zhou, Peilun Liu:
Bearing compound fault diagnosis based on enhanced variational mode extraction algorithm. 73-78 - Jiahui Wang, Lin Ma, Ankang Chen, Qiannan Liu, Mingshun Ma:
Fault State Prediction Model of Repaired Equipment Considering Maintenance Effect. 79-88 - Jie Meng, Jiji Cai, Liang Chang:
A causal graph-based framework for satellite health monitoring. 89-98 - Zhuang Ye, Jianbo Yu, Pu Yang, Shang Yue, Ruixu Zhou, Mingyan Ma:
Generative Adversarial Network for State of Health Estimation of Lithium-ion Batteries. 99-104 - Zhenghong Wu, Hongkai Jiang, Sicheng Zhang, Xin Wang, Haidong Shao, Haoxuan Dou:
Intelligent fault diagnosis of rolling bearing based on a deep transfer learning network. 105-111 - Mengqi Miao, Jianbo Yu, Pu Yang, Shang Yue, Ruixu Zhou:
Selective Domain Adaptation Network for Lithium-ion Battery Health Monitoring. 112-118 - Thiagarajan Ravichandran, Yuan Liu, Amar Kumar, Alka Srivastava:
Convolutional Neural Networks for Gas Turbine Exhaust Gas Temperature and Power Predictions. 119-127 - Mehrnaz Mirzaei, Marzieh Hashemzadeh Sadat, Farnoosh Naderkhani:
Application of Machine Learning for Anomaly Detection in Printed Circuit Boards Imbalance Date Set. 128-133 - Hasan Rasay, Fariba Azizi, Mehrnaz Salmani, Farnoosh Naderkhani:
A Reinforcement Learning Algorithm for Optimal Dynamic Policies of Joint Condition-based Maintenance and Condition-based Production. 134-138 - Subrata Mukherjee, Deepak Kumar, Obaid Elshafiey, Lalita Udpa, Yiming Deng:
Accurate Material Characterization of Wideband RF Signals via Registration-based Curve Fitting Model using Microstrip Transmission Line. 139-145 - Ali Safian, Xihui Liang:
Bearing fault detection and fault size estimation using an integrated PVDF transducer. 146-152 - Daniel O. Williams, Zhaojun Steven Li, Afsaneh Ghanavati:
Mitigating Electrical Losses Through a Programmable Smart Energy Advanced Metering Infrastructure System. 153-157 - Yanik Koch, Michel Fett, Eckhard Kirchner:
Angular measurement with a gear wheel as a material measure - Extension as absolute sensor. 158-165 - Haoyuan Shen, Xueyi Wang, Liqun Fu, Jiawei Xiong:
Gear Fault Diagnosis Based on Short-time Fourier Transform and Deep Residual Network under Multiple Operation Conditions. 166-171 - Xian Yeow Lee, Aman Kumar, Lasitha Vidyaratne, Aniruddha Rajendra Rao, Ahmed K. Farahat, Chetan Gupta:
An ensemble of convolution-based methods for fault detection using vibration signals. 172-179 - Parvathy Sobha, Midhun Xavier, Praneeth Chandran:
A Comprehensive Approach for Gearbox Fault Detection and Diagnosis Using Sequential Neural Networks. 180-185 - Matthias Kreuzer, Walter Kellermann:
1-D Residual Convolutional Neural Network coupled with Data Augmentation and Regularization for the ICPHM 2023 Data Challenge. 186-191 - Peng Liu:
Vibration Time Series Classification using Parallel Computing and XGBoost. 192-199 - Hasan Rasay, Fariba Azizi, Mehrnaz Salmani, Farnoosh Naderkhani:
A Reinforcement Learning Algorithm for Optimal Dynamic Policies of Joint Condition-based Maintenance and Condition-based Production. 200-204 - Zhenning Li, Hongkai Jiang, Shaowei Liu, Ruixin Wang:
Fault diagnosis of rolling bearing using a transfer ensemble deep reinforcement learning method. 205-211 - Masuda Akter Tonima, Austin Dehart, Deniz Tabakci, Piramon Tisapramotkul, Andrew Munro-West, Aarushi Mehra, Tina Shoa:
Electrochemical Impedance Spectroscopy (EIS) and Machine Learning based Battery State of Health (SoH) Estimation. 212-223 - Ao Ding, Yong Qin, Biao Wang, Limin Jia:
A Class-Added Continual Learning Method for Motor Fault Diagnosis Based on Knowledge Distillation of Representation Proximity Behavior. 224-231 - Matthias Kreuzer, David Schmidt, Simon Wokusch, Walter Kellermann:
Airborne Sound Analysis for the Detection of Bearing Faults in Railway Vehicles with Real-World Data. 232-238 - Zhong Ren, Xianrong Qin, Qing Zhang, Yuantao Sun:
Damage Evolution Characterization of Low Carbon Alloy Steel Based on Multiaxial Fatigue Test and DIC. 239-245 - Yamini Devidas Kotriwar, Obaid Elshafiey, Lei Peng, Zi Li, Vijay Srinivasan, Eric Davis, Yiming Deng:
Gradient feature-based method for Defect Detection of Carbon Fiber Reinforced Polymer Materials. 246-252 - Aungshula Chowdhury, Michael G. Lipsett:
Modeling Operational Risk to Improve Reliability of Unmanned Aerial Vehicles. 253-264 - Lucas Dimitri, Jonathan Liscouët:
Optimizing Flight Control of Unmanned Aerial Vehicles with Physics-Based Reliability Models. 265-273 - Chen Chen, Meng Mei, Haidong Shao, Pei Liang:
A support tensor machine-based fault diagnosis method for railway turnout. 274-281 - Na Zhang, Lixiang Duan, Xiaofeng Li, Xiangwu Liu:
Imbalanced fault diagnosis of planetary gearboxes based on noise enhancement and threshold adaptive Siamese decoupled network. 282-290 - Geng Xu, Mingxin Gao, Feng Liu, Yang Liu:
Research on Visual Detection Methods and Development Trends of Surface Defects of Urban Tunnels. 291-295 - Ryosuke Takayama, Masanao Natsumeda, Takehisa Yairi:
A semi-supervised RUL prediction with likelihood-based pseudo labeling for suspension histories. 296-303 - José Joaquín Mendoza Lopetegui, Gianluca Papa, Mara Tanelli:
Data-driven Health Monitoring and Anomaly Detection in Aircraft Shock Absorbers. 304-311 - Giovanni Di Nuzzo, Horst Lewitschnig, Marc Tuellmann, Sven Rzepka, Alexander Otto:
A Data-driven Condition Monitoring method to predict the Remaining Useful Life of SiC Power Modules for Traction Inverters. 312-319 - Giulia Murtas, Henrique Cabral, Elena Tsiporkova:
Data-driven estimation of blade icing risk in wind turbines. 320-327 - Jianqun Zhang, Qing Zhang, Xianrong Qin, Yuantao Sun:
2D Characterization Based on MSGMD And Its Application in Gearbox Fault Diagnosis. 328-334 - Ethan Wescoat, Vinita Gangaram Jansari, Laine Mears:
Optimizing Data Training Quantity for Bearing Condition Monitoring. 335-342 - Fabian Fingerhut, Sarah Klein, Mathias Verbeke, Sreeraj Rajendran, Elena Tsiporkova:
Multi-view contextual performance profiling in rotating machinery. 343-350 - Rocco Cassandro, Quing Li, Zhaojun Steven Li:
An Entropy-based Data Reduction Method for Data Preprocessing. 351-356 - Brett Sicard, Quade Butler, Youssef Ziada, S. Andrew Gadsden:
Experimental Setups for Linear Feed Drive Predictive Maintenance: A Review. 357-367 - Yan Li, Navid Zaman, Jacek Stecki, Chris Stecki:
State Reconstruction: Generating a Reference for Improved Diagnostics. 368-371
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