Digital twin-driven remaining useful life prediction for gear performance degradation: A review
B He, L Liu, D Zhang - Journal of Computing and …, 2021 - asmedigitalcollection.asme.org
As a transmission component, the gear has been obtained widespread attention. The
remaining useful life (RUL) prediction of gear is critical to the prognostics health …
remaining useful life (RUL) prediction of gear is critical to the prognostics health …
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 …
[HTML][HTML] Prediction of future capacity and internal resistance of Li-ion cells from one cycle of input data
C Strange, G Dos Reis - Energy and AI, 2021 - Elsevier
There is a large demand for models able to predict the future capacity retention and internal
resistance (IR) of Lithium-ion battery cells with as little testing as possible. We provide a data …
resistance (IR) of Lithium-ion battery cells with as little testing as possible. We provide a data …
Causal augmented ConvNet: A temporal memory dilated convolution model for long-sequence time series prediction
A number of deep learning models have been proposed to capture the inherent information
in multivariate time series signals. However, most of the existing models are suboptimal …
in multivariate time series signals. However, most of the existing models are suboptimal …
Remaining useful life estimation using long short-term memory neural networks and deep fusion
Y Zhang, P Hutchinson, NAJ Lieven… - IEEE …, 2020 - ieeexplore.ieee.org
Estimation of Remaining Useful Life (RUL) is a crucial task in Prognostics and Health
Management (PHM) for condition-based maintenance of machinery. In order to transmit and …
Management (PHM) for condition-based maintenance of machinery. In order to transmit and …
Stewart: Stacking ensemble for white-box adversarial attacks towards more resilient data-driven predictive maintenance
Abstract Industrial Internet of Things (I-IoT) is a network of devices that focus on monitoring
industrial assets and continuously collecting data. This data can be utilized by Machine …
industrial assets and continuously collecting data. This data can be utilized by Machine …
Remaining useful life estimation of aircraft engines using a joint deep learning model based on TCNN and transformer
HK Wang, Y Cheng, K Song - Computational Intelligence and …, 2021 - Wiley Online Library
The remaining useful life estimation is a key technology in prognostics and health
management (PHM) systems for a new generation of aircraft engines. With the increase in …
management (PHM) systems for a new generation of aircraft engines. With the increase in …
A predictive maintenance model for flexible manufacturing in the context of industry 4.0
GM Sang, L Xu, P de Vrieze - Frontiers in big Data, 2021 - frontiersin.org
The Industry 4.0 paradigm is the focus of modern manufacturing system design. The
integration of cutting-edge technologies such as the Internet of things, cyber–physical …
integration of cutting-edge technologies such as the Internet of things, cyber–physical …
Predictive maintenance in industry 4.0
In the context of Industry 4.0, the manufacturing related processes have shifted from
conventional processes within one organization to collaborative processes cross different …
conventional processes within one organization to collaborative processes cross different …
Dowell: diversity-induced optimally weighted ensemble learner for predictive maintenance of industrial internet of things devices
The Industrial Internet of Things (I-IoT) enables a smarter maintenance approach for various
industrial applications, such as manufacturing, logistics, etc. This approach is based on …
industrial applications, such as manufacturing, logistics, etc. This approach is based on …