À̸§ KSPHM À̸ÞÀÏ phm@phm.or.kr
ÀÛ¼ºÀÏ 2023-05-30 Á¶È¸¼ö 293
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[PHM News Letter Vol. 20] PHM °ü·Ã Çмú Àú³Î ¹× ³í¹®

Maxwell Toothman, Birgit Braun, Scott J. Bury, James Moyne, Dawn M. Tilbury, Yixin Ye, Kira Barton, A digital twin framework for prognostics and health management, Computers in Industry, Volume 150, 2023, 103948, ISSN 0166-3615,

https://doi.org/10.1016/j.compind.2023.103948.

(https://www.sciencedirect.com/science/article/pii/S0166361523000982)


Hao Wu, Xing'ang Xu, Chuanfu Xin, Yichen Liu, Runze Rao, Zhongjie Li, Dan Zhang, Yongxi Wu, Senzhe Han, Intelligent fault diagnosis for triboelectric nanogenerators via a novel deep learning framework, Expert Systems with Applications, Volume 226, 2023, 120244, ISSN 0957-4174,

https://doi.org/10.1016/j.eswa.2023.120244.

(https://www.sciencedirect.com/science/article/pii/S0957417423007467)


Jingyuan Zhao, Andrew F. Burke, Battery prognostics and health management for electric vehicles under industry 4.0, Journal of Energy Chemistry, 2023, ISSN 2095-4956,

https://doi.org/10.1016/j.jechem.2023.04.042.

(https://www.sciencedirect.com/science/article/pii/S2095495623002711)


Chao Yang, Baoping Cai, Qibing Wu, Chenyushu Wang, Weifeng Ge, Zhiming Hu, Wei Zhu, Lei Zhang, Longting Wang, Digital twin-driven fault diagnosis method for composite faults by combining virtual and real data, Journal of Industrial Information Integration, Volume 33, 2023, 100469, ISSN 2452-414X, 

https://doi.org/10.1016/j.jii.2023.100469.

(https://www.sciencedirect.com/science/article/pii/S2452414X23000420)


Sourajit Behera, Rajiv Misra, A multi-model data-fusion based deep transfer learning for improved remaining useful life estimation for IIOT based systems, Engineering Applications of Artificial Intelligence, Volume 119, 2023, 105712, ISSN 0952-1976,

https://doi.org/10.1016/j.engappai.2022.105712.

(https://www.sciencedirect.com/science/article/pii/S0952197622007023) 


Zhonghai Ma, Haitao Liao, Jianhang Gao, Songlin Nie, Yugang Geng, Physics-Informed Machine Learning for Degradation Modeling of an Electro-Hydrostatic Actuator System, Reliability Engineering & System Safety, Volume 229, 2023, 108898, ISSN 0951-8320,

https://doi.org/10.1016/j.ress.2022.108898.

(https://www.sciencedirect.com/science/article/pii/S0951832022005130) 


Songlin Nie, Jianhang Gao, Zhonghai Ma, Fanglong Yin, Hui Ji, An online data-driven approach for performance prediction of electro-hydrostatic actuator with thermal-hydraulic modeling, Reliability Engineering & System Safety, Volume 236, 2023, 109289, ISSN 0951-8320,

https://doi.org/10.1016/j.ress.2023.109289.

(https://www.sciencedirect.com/science/article/pii/S0951832023002041) 


Myeongsun Kwak, Jongsoo Lee, Diagnosis-based domain-adaptive design using designable data augmentation and Bayesian transfer learning: Target design estimation and validation, Applied Soft Computing, 2023, 110459, ISSN 1568-4946,

https://doi.org/10.1016/j.asoc.2023.110459.

(https://www.sciencedirect.com/science/article/pii/S1568494623004775) 


Yicheng Sun, Yuqian Lu, Jinsong Bao, Fei Tao, Prognostics and health management via long short-term digital twins, Journal of Manufacturing Systems, Volume 68, 2023, Pages 560-575, ISSN 0278-6125,

https://doi.org/10.1016/j.jmsy.2023.05.023.

(https://www.sciencedirect.com/science/article/pii/S0278612523000973)


Anass Akrim, Christian Gogu, Rob Vingerhoeds, Michel Salaün, Self-Supervised Learning for data scarcity in a fatigue damage prognostic problem, Engineering Applications of Artificial Intelligence, Volume 120, 2023, 105837, ISSN 0952-1976,

https://doi.org/10.1016/j.engappai.2023.105837.

(https://www.sciencedirect.com/science/article/pii/S0952197623000210) 


Jianhai Yan, Zhen He, Shuguang He, Multitask learning of health state assessment and remaining useful life prediction for sensor-equipped machines, Reliability Engineering & System Safety, Volume 234, 2023, 109141, ISSN 0951-8320,

https://doi.org/10.1016/j.ress.2023.109141.

(https://www.sciencedirect.com/science/article/pii/S095183202300056X) 


Darshankumar Bhat, Stefan Muench, Mike Roellig, Application of machine learning algorithms in prognostics and health monitoring of electronic systems: A review, e-Prime - Advances in Electrical Engineering, Electronics and Energy, Volume 4, 2023, 100166, ISSN 2772-6711,

https://doi.org/10.1016/j.prime.2023.100166.

(https://www.sciencedirect.com/science/article/pii/S277267112300061X


Xinyu Zou, Laifa Tao, Lulu Sun, Chao Wang, Jian Ma, Chen Lu, A case-learning-based paradigm for quantitative recommendation of fault diagnosis algorithms: A case study of gearbox, Reliability Engineering & System Safety, Volume 237, 2023, 109372, ISSN 0951-8320,

https://doi.org/10.1016/j.ress.2023.109372.

(https://www.sciencedirect.com/science/article/pii/S0951832023002867) 


Yi Qin, Jiahong Yang, Jianghong Zhou, Huayan Pu, Yongfang Mao, A new supervised multi-head self-attention autoencoder for health indicator construction and similarity-based machinery RUL prediction, Advanced Engineering Informatics, Volume 56, 2023, 101973, ISSN 1474-0346,

https://doi.org/10.1016/j.aei.2023.101973.

(https://www.sciencedirect.com/science/article/pii/S1474034623001015) 


Junho Lee, Younghun Lee, Namsu Kim, Detection and analysis of shaft misalignment in application of production and logistics systems using motor current signature analysis, Expert Systems with Applications, Volume 217, 2023, 119463, ISSN 0957-4174,

https://doi.org/10.1016/j.eswa.2022.119463.

(https://www.sciencedirect.com/science/article/pii/S0957417422024824) 


ÀÌÀü±Û [PHM News Letter Vol. 20] International Journal of Production Research ¾È³»
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