Predictive maintenance (PdM) is a policy applying data and analytics to predict when one of
the components in a real system has been destroyed, and some anomalies appear so that …

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 …

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 …

Prognostics and health management applications rely heavily on predicting industrial
equipment's remaining useful life (RUL). The traditional RUL prediction approaches mainly …

Accurate remaining useful life (RUL) prediction is of great importance for predictive
maintenance. With the recent advancements in sensor technology and artificial intelligence …

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 …

Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of
damage propagation and aging of operating systems during working conditions. More …

Accurate estimation and prediction of the state-of-health (SOH) and remaining useful life
(RUL) are fundamental to optimal maintenance strategies formulation for prognostics and …

Due to the complicated production mechanism in multivariate industrial processes, different
dynamic features of variables raise challenges to traditional data-driven process monitoring …

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 …