Physics-informed machine learning in prognostics and health management: State of the art and challenges

•Systematic bibliometric analysis of PIML in PHM.•Novel perspectives for PIML from the “Informed knowledge forms” and “Informed methods”.•Taxonomy of PIML approaches in PHM.•Highlight remaining challenges and future perspectives based on this review. Prognostics and health management (PHM) plays a c...

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Vydané v:	Applied mathematical modelling Ročník 124; s. 325 - 352
Hlavní autori:	DENG, Weikun, NGUYEN, Khanh T.P., MEDJAHER, Kamal, GOGU, Christian, MORIO, Jérôme
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.12.2023 Elsevier
Predmet:	Engineering Sciences Knowledge Materials Physics-constraint learning Physics-embedded algorithm structure Physics-informed input space Physics-informed machine learning Prognostics and health management ANN CNN DNN GNN NMAE Physics-informed machine learning SVM Knowledge PDE RNN PHM PBM MSE Physics-embedded algorithm structure LSTM NODE RUL RMSE Prognostics and health management PCA FCN MAE ROM Physics-constraint learning CRA KSVD NMSE VAE Physics-informed input space PIML DRM
ISSN:	0307-904X, 1872-8480
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