[HTML][HTML] Marine systems and equipment prognostics and health management: a systematic review from health condition monitoring to maintenance strategy
P Zhang, Z Gao, L Cao, F Dong, Y Zou, K Wang… - Machines, 2022 - mdpi.com
Prognostics and health management (PHM) is an essential means to optimize resource
allocation and improve the intelligent operation and maintenance (O&M) efficiency of marine …
allocation and improve the intelligent operation and maintenance (O&M) efficiency of marine …
Challenges of machine learning-based RUL prognosis: A review on NASA's C-MAPSS data set
S Vollert, A Theissler - 2021 26th IEEE international conference …, 2021 - ieeexplore.ieee.org
The estimation of a system's or a component's remaining useful life (RUL) is considered the
most complex task in predictive maintenance, at the same time the most beneficial one. In …
most complex task in predictive maintenance, at the same time the most beneficial one. In …
A deep feature learning method for remaining useful life prediction of drilling pumps
J Guo, JL Wan, Y Yang, L Dai, A Tang, B Huang… - Energy, 2023 - Elsevier
Abstract Remaining Useful Life (RUL) prediction of drilling pumps, pivotal components in
fossil energy production, is essential for efficient maintenance and safe operation of such …
fossil energy production, is essential for efficient maintenance and safe operation of such …
Data-driven bearing health management using a novel multi-scale fused feature and gated recurrent unit
Remaining useful life (RUL) prediction plays a crucial role in bearing health management
which can guarantee the rotating machinery systems' safety and reliability. This paper …
which can guarantee the rotating machinery systems' safety and reliability. This paper …
[HTML][HTML] Health indicator for machine condition monitoring built in the latent space of a deep autoencoder
A González-Muñiz, I Diaz, AA Cuadrado… - Reliability Engineering & …, 2022 - Elsevier
The construction of effective health indicators plays a key role in the engineering systems
field: they reflect the degradation degree of the system under study, thus providing vital …
field: they reflect the degradation degree of the system under study, thus providing vital …
[HTML][HTML] Intelligent health indicator construction for prognostics of composite structures utilizing a semi-supervised deep neural network and SHM data
A health indicator (HI) is a valuable index demonstrating the health level of an engineering
system or structure, which is a direct intermediate connection between raw signals collected …
system or structure, which is a direct intermediate connection between raw signals collected …
A sparse domain adaption network for remaining useful life prediction of rolling bearings under different working conditions
M Miao, J Yu, Z Zhao - Reliability Engineering & System Safety, 2022 - Elsevier
As a key component in the machinery, the health of bearings directly affects working
performance of machinery. Recently, many data-driven methods have been proposed to …
performance of machinery. Recently, many data-driven methods have been proposed to …
Dual-thread gated recurrent unit for gear remaining useful life prediction
Remaining useful life (RUL) prediction can provide a foundation for the operation and
maintenance of industrial equipment. In order to improve the predictive ability for the …
maintenance of industrial equipment. In order to improve the predictive ability for the …
Automatic multi-differential deep learning and its application to machine remaining useful life prediction
Different levels of characteristic information cannot be mined using various feature extraction
modes in most neural networks, and thus, a novel method called the automatic multi …
modes in most neural networks, and thus, a novel method called the automatic multi …
Explainable, interpretable, and trustworthy AI for an intelligent digital twin: A case study on remaining useful life
K Kobayashi, SB Alam - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Artificial intelligence (AI) and Machine learning (ML) are increasingly used for digital twin
development in energy and engineering systems, but these models must be fair, unbiased …
development in energy and engineering systems, but these models must be fair, unbiased …