Weikun DENG - Admis au titre de docteur


dwk_study@163.com
weikun.deng@enit.fr
Identifiant ORCID 0000000251954184

Doctorat Génie Industriel


Thèse soutenue le 7 novembre 2024 - Institut National Polytechnique de Toulouse

Ecole doctorale : SYSTEMES

Sujet : Amélioration du diagnostic et du pronostic dans des conditions de données rares et de connaissances limitées par l'apprentissage automatique informé par la physique et auto-supervisé

Mots-clés de la thèse : Pronostic et Gestion de la santé,Données éparses,Connaissances rares,PIML,SSL,Modèle générique,

Direction de thèse : Kamal MEDJAHER

Co-direction de thèse : Thi Phuong Khanh NGUYEN

Unité de recherche : LGP - Laboratoire Génie de Production EA 1905 - Tarbes

Master - Academic master's degree

obtenu en avril 2020 - Northwestern Polytechnical University
Option : Aerospace Propulsion Theory and Engineering

Production scientifique

- Weikun DENG, Khanh T.P. NGUYEN, Christian GOGU, Jérôme MORIO, Kamal MEDJAHER, Hung LE, Dazhong WU 2024. A Novel PIML Architecture with Innovative Learning Paradigm Applied in Battery Prognostics   CODIT 2024, ——, https://ieeexplore.ieee.org/xpl/conhome/1803079/all-proceedings
- Weikun DENG, Khanh T.P. NGUYEN, Kamal MEDJAHER, Christian GOGU, Jérôme MORIO 2024. Enhancing Prognostics for Sparse Labeled Data Using Advanced Contrastive Self-Supervised Learning with Downstream Integration   Engineering Applications of Artificial Intelligence, _, https://doi.org/10.1016/j.engappai.2024.109268
- Weikun DENG, Hung LE, Christian GOGU, Khanh T.P. NGUYEN, Kamal MEDJAHER, Jérôme MORIO, Dazhong WU 2024. Generic Physics-Informed Machine Learning Framework for Battery Remaining Useful Life Prediction Using Small Early-Stage Lifecycle Data   Applied Energy, _, http://dx.doi.org/10.2139/ssrn.4770354
- Weikun Deng, Fabio Ardiani, Khanh T.P. Nguyen, Mourad Benoussaad, Kamal Medjaher 2024. Physics informed machine learning model for inverse dynamics in robotic manipulators   Applied Soft Computing, Volume 163 , https://doi.org/10.1016/j.asoc.2024.111877
- Weikun DENG, Khanh T.P. NGUYEN, Christian GOGU, Jérôme MORIO, Kamal MEDJAHER 2023. A Few-Shot Learning Framework for Rotor Unbalance and Shaft Crack Fault Diagnostic Based on Physics-Informed Neural Network   Structural Health Monitoring 2023, _, 10.12783/shm2023/36985
- Weikun Deng, Khanh T P Nguyen, Kamal Medjaher, Christian Gogu, Jérôme Morio 2023. Bearings RUL prediction based on contrastive self-supervised learning   IFAC-SectionsOnLine, 56, pp.11906-11911, https://doi.org/10.1016/j.ifacol.2023.10.604
- Weikun Deng, Khanh T.P. Nguyen, Kamal Medjaher, Christian Gogu, Jérôme Morio 2023. Physics-informed machine learning in prognostics and health management: State of the art and challenges   Applied Mathematical Modelling, 124, pp.325-352, https://doi.org/10.1016/j.apm.2023.07.011
- Weikun Deng, Khanh T.P. Nguyen, Kamal Medjaher, Christian Gogu, Jérôme Morio 2023. Rotor dynamics informed deep learning for detection, identification, and localization of shaft crack and unbalance defects   Advanced Engineering Informatics, 58, pp.102128, https://doi.org/10.1016/j.aei.2023.102128
- Weikun DENG, Khanh T.P. NGUYEN, Kamal MEDJAHER 2022. Physics Informed Self Supervised Learning For Fault Diagnostics and Prognostics in the Context of Sparse and Noisy Data   PHM Society European Conference 2022, 7(1), 574–576, 10.36001/phme.2022.v7i1.3298
- Weikun Deng, Khanh T P Nguyen, Christian Gogu, Jérôme Morio, Kamal Medjaher 2022. Physics-informed Lightweight Temporal Convolution Networks for Fault Prognostics Associated to Bearing Stiffness Degradation   PHM Society European Conference 2022, 7, pp.118-125, 10.36001/phme.2022.v7i1.3365
Dernière mise à jour le 4 janvier 2025