A systematic guide for predicting remaining useful life with machine learning
T Berghout, M Benbouzid - Electronics, 2022 - mdpi.com
Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of
damage propagation and aging of operating systems during working conditions. More …
damage propagation and aging of operating systems during working conditions. More …
DeepThink IoT: the strength of deep learning in internet of things
Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …
revolutionized technology in the twenty-first century, enabling humans and machines to …
Bi-LSTM-based two-stream network for machine remaining useful life prediction
In industry, prognostics and health management (PHM) is used to improve the system
reliability and efficiency. In PHM, remaining useful life (RUL) prediction plays a key role in …
reliability and efficiency. In PHM, remaining useful life (RUL) prediction plays a key role in …
Spatio-temporal fusion attention: A novel approach for remaining useful life prediction based on graph neural network
Prognostics and health management applications rely heavily on predicting industrial
equipment's remaining useful life (RUL). The traditional RUL prediction approaches mainly …
equipment's remaining useful life (RUL). The traditional RUL prediction approaches mainly …
A novel performance trend prediction approach using ENBLS with GWO
H Zhao, P Zhang, R Zhang, R Yao… - … Science and Technology, 2022 - iopscience.iop.org
Bearings are a core component of rotating machinery, and directly affect its reliability and
operational efficiency. Effective evaluation of a bearing's operational state is key to ensuring …
operational efficiency. Effective evaluation of a bearing's operational state is key to ensuring …
Prediction interval estimation of aeroengine remaining useful life based on bidirectional long short-term memory network
Reliable and accurate aeroengine remaining useful life (RUL) prediction plays a key role in
the aeroengine prognostics and health management (PHM) system. However, due to the …
the aeroengine prognostics and health management (PHM) system. However, due to the …
LSTMED: An uneven dynamic process monitoring method based on LSTM and Autoencoder neural network
Due to the complicated production mechanism in multivariate industrial processes, different
dynamic features of variables raise challenges to traditional data-driven process monitoring …
dynamic features of variables raise challenges to traditional data-driven process monitoring …
Residual convolution long short-term memory network for machines remaining useful life prediction and uncertainty quantification
Recently, deep learning is widely used in the field of remaining useful life (RUL) prediction.
Among various deep learning technologies, recurrent neural network (RNN) and its variant …
Among various deep learning technologies, recurrent neural network (RNN) and its variant …
Slow-varying dynamics-assisted temporal capsule network for machinery remaining useful life estimation
Capsule network (CapsNet) acts as a promising alternative to the typical convolutional
neural network, which is the dominant network to develop the remaining useful life (RUL) …
neural network, which is the dominant network to develop the remaining useful life (RUL) …
Position encoding based convolutional neural networks for machine remaining useful life prediction
Accurate remaining useful life (RUL) prediction is important in industrial systems. It prevents
machines from working under failure conditions, and ensures that the industrial system …
machines from working under failure conditions, and ensures that the industrial system …