[HTML][HTML] Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods
C Ferreira, G Gonçalves - Journal of Manufacturing Systems, 2022 - Elsevier
Abstract Approaches such as Cyber-Physical Systems (CPS), Internet of Things (IoT),
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …
A review on methods for state of health forecasting of lithium-ion batteries applicable in real-world operational conditions
F von Bülow, T Meisen - Journal of Energy Storage, 2023 - Elsevier
The ageing of Lithium-ion batteries can be described as change of state of health (∆ SOH). It
depends on the battery's operation during charging, discharging, and rest phases. Mapping …
depends on the battery's operation during charging, discharging, and rest phases. Mapping …
A dual-LSTM framework combining change point detection and remaining useful life prediction
Abstract Remaining Useful Life (RUL) prediction is a key task of Condition-based
Maintenance (CBM). The massive data collected from multiple sensors enables monitoring …
Maintenance (CBM). The massive data collected from multiple sensors enables monitoring …
Artificial intelligence in prognostics and health management of engineering systems
S Ochella, M Shafiee, F Dinmohammadi - Engineering Applications of …, 2022 - Elsevier
Prognostics and health management (PHM) has become a crucial aspect of the
management of engineering systems and structures, where sensor hardware and decision …
management of engineering systems and structures, where sensor hardware and decision …
A directed acyclic graph network combined with CNN and LSTM for remaining useful life prediction
Accurate and timely prediction of remaining useful life (RUL) of a machine enables the
machine to have an appropriate operation and maintenance decision. Data-driven RUL …
machine to have an appropriate operation and maintenance decision. Data-driven RUL …
An ensemble framework based on convolutional bi-directional LSTM with multiple time windows for remaining useful life estimation
Effectively estimating remaining useful life (RUL) is crucially important for evaluating
machine health. In the industry, there exists a high degree of inconsistency among the …
machine health. In the industry, there exists a high degree of inconsistency among the …
A deep learning model for remaining useful life prediction of aircraft turbofan engine on C-MAPSS dataset
In the era of industry 4.0, safety, efficiency and reliability of industrial machinery is an
elementary concern in trade sectors. The accurate remaining useful life (RUL) prediction of …
elementary concern in trade sectors. The accurate remaining useful life (RUL) prediction of …
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 change point detection integrated remaining useful life estimation model under variable operating conditions
By informing the onset of the degradation process, health status evaluation serves as a
significant preliminary step for reliable remaining useful life (RUL) estimation of complex …
significant preliminary step for reliable remaining useful life (RUL) estimation of complex …
Least squares smoothed k-nearest neighbors online prediction of the remaining useful life of a NASA turbofan
An accurate prediction of the Remaining Useful Life (RUL) of aircraft engines plays a
fundamental role in the aerospace field since it is both mission and safety critical. In fact, a …
fundamental role in the aerospace field since it is both mission and safety critical. In fact, a …