Challenges and opportunities of AI-enabled monitoring, diagnosis & prognosis: A review

Z Zhao, J Wu, T Li, C Sun, R Yan, X Chen - Chinese Journal of Mechanical …, 2021 - Springer
Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …

Analysis of frontier digital technologies in continuing airworthiness management frameworks and applications

T Raoofi, S Yasar - Aircraft Engineering and Aerospace Technology, 2023 - emerald.com
Purpose This study aims to elaborate on the existing link between maintenance practices
and the digital world while also highlighting any unaddressed potential for digital …

A survey of modeling for prognosis and health management of industrial equipment

YA Yucesan, A Dourado, FAC Viana - Advanced Engineering Informatics, 2021 - Elsevier
Prognosis and health management plays an important role in the control of costs associated
with operating large industrial equipment, such as wind turbines and aircraft. It is only fair …

Time-varying trajectory modeling via dynamic governing network for remaining useful life prediction

Z Zhou, T Li, Z Zhao, C Sun, X Chen, R Yan… - Mechanical Systems and …, 2023 - Elsevier
Remaining useful life (RUL) prediction is highly demanded in modern industry as it provides
a scheduling basis for predictive maintenance. Recently, intelligent data-driven methods …

Cumulative damage modeling with recurrent neural networks

RG Nascimento, FAC Viana - AIAA Journal, 2020 - arc.aiaa.org
Maintenance of engineering assets (for example, aircraft, jet engines, and wind turbines) is a
profitable business. Unfortunately, building models that estimate remaining useful life for …

Computational framework for real-time diagnostics and prognostics of aircraft actuation systems

PC Berri, MDL Dalla Vedova, L Mainini - Computers in Industry, 2021 - Elsevier
Prognostics and health management (PHM) are emerging approaches to product life cycle
that will maintain system safety and improve reliability, while reducing operating and …

Learning for predictions: Real-time reliability assessment of aerospace systems

PC Berri, MDL Dalla Vedova, L Mainini - AIAA Journal, 2022 - arc.aiaa.org
Prognostics and health management aim to predict the remaining useful life (RUL) of a
system and to allow a timely planning of replacement of components, limiting the need for …

[HTML][HTML] Physics-aware multifidelity Bayesian optimization: A generalized formulation

F Di Fiore, L Mainini - Computers & Structures, 2024 - Elsevier
The adoption of high-fidelity models for many-query optimization problems is majorly limited
by the significant computational cost required for their evaluation at every query. Multifidelity …

Knowledge informed machine learning using a weibull-based loss function

T von Hahn, CK Mechefske - arXiv preprint arXiv:2201.01769, 2022 - arxiv.org
Machine learning can be enhanced through the integration of external knowledge. This
method, called knowledge informed machine learning, is also applicable within the field of …

Fault detection and diagnosis in spacecraft electrical power systems

MA Carbone, KA Loparo - Journal of Aerospace Information Systems, 2023 - arc.aiaa.org
The ability to accurately identify and isolate failures in the electrical power system (EPS) is
critical to ensure the reliability of spacecraft. This paper proposes a novel solution to the …