Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges
The computerized simulations of physical and socio-economic systems have proliferated in
the past decade, at the same time, the capability to develop high-fidelity system predictive …
the past decade, at the same time, the capability to develop high-fidelity system predictive …
Recent advances in reliability analysis of aeroengine rotor system: a review
Purpose To provide valuable information for scholars to grasp the current situations,
hotspots and future development trends of reliability analysis area. Design/methodology …
hotspots and future development trends of reliability analysis area. Design/methodology …
Probabilistic framework for fatigue life assessment of notched components under size effects
Structural integrity assessments with discontinuities are critical for ensuring operational life
and reliability of engineering components. In this work, through combining with the …
and reliability of engineering components. In this work, through combining with the …
A novel fault diagnosis method based on CNN and LSTM and its application in fault diagnosis for complex systems
T Huang, Q Zhang, X Tang, S Zhao, X Lu - Artificial Intelligence Review, 2022 - Springer
Fault diagnosis plays an important role in actual production activities. As large amounts of
data can be collected efficiently and economically, data-driven methods based on deep …
data can be collected efficiently and economically, data-driven methods based on deep …
Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions
Intelligent data-driven system prognostic methods have been popularly developed in the
recent years. Despite the promising results, most approaches assume the training and …
recent years. Despite the promising results, most approaches assume the training and …
Probabilistic fatigue modelling of metallic materials under notch and size effect using the weakest link theory
Notch fatigue analysis is vital for structural integrity design, while efficient fatigue models
coupling notch and size effect are still lacking, which are highly desired for fatigue design of …
coupling notch and size effect are still lacking, which are highly desired for fatigue design of …
Computational-experimental approaches for fatigue reliability assessment of turbine bladed disks
In the present study, a computational-experimental framework is developed for fatigue
reliability assessment of turbine bladed disks. Within the framework, the overspeed testing is …
reliability assessment of turbine bladed disks. Within the framework, the overspeed testing is …
Deep learning regression-based stratified probabilistic combined cycle fatigue damage evaluation for turbine bladed disks
Probabilistic combined cycle fatigue (CCF) damage evaluation involves complex large-scale
simulations of low cycle fatigue (LCF) damage, high cycle fatigue (HCF) damage and …
simulations of low cycle fatigue (LCF) damage, high cycle fatigue (HCF) damage and …
Transfer learning with deep recurrent neural networks for remaining useful life estimation
Prognostics, such as remaining useful life (RUL) prediction, is a crucial task in condition-
based maintenance. A major challenge in data-driven prognostics is the difficulty of …
based maintenance. A major challenge in data-driven prognostics is the difficulty of …
[HTML][HTML] A data-driven roadmap for creep-fatigue reliability assessment and its implementation in low-pressure turbine disk at elevated temperatures
High-reliability life design process not only can ensure system safety in service, but also can
provide scientific life management during the maintenance period. The objective of the …
provide scientific life management during the maintenance period. The objective of the …