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 …
A multimodal and hybrid deep neural network model for remaining useful life estimation
Aging critical infrastructures and valuable machineries together with recent catastrophic
incidents such as the collapse of Morandi bridge calls for an urgent quest to design …
incidents such as the collapse of Morandi bridge calls for an urgent quest to design …
Multi-scale dense gate recurrent unit networks for bearing remaining useful life prediction
Internet of thing (IoT), with the rapid development, is the systematic combination of physical
process, information and communication technologies. Industry internet of thing (IIoT), as the …
process, information and communication technologies. Industry internet of thing (IIoT), as the …
Localization of myocardial infarction from multi-lead ECG signals using multiscale analysis and convolutional neural network
RK Tripathy, A Bhattacharyya… - IEEE Sensors …, 2019 - ieeexplore.ieee.org
The occlusion in one of the coronary arteries of the heart leads to the cardiac ailment,
myocardial infarction (MI). The localization of MI based on the investigation of the …
myocardial infarction (MI). The localization of MI based on the investigation of the …
Homecare-oriented intelligent long-term monitoring of blood pressure using electrocardiogram signals
Long-term blood pressure (BP) monitoring is a widely used approach in a homecare
intelligent system. However, BP is usually measured using cuff-based devices with tedious …
intelligent system. However, BP is usually measured using cuff-based devices with tedious …
Deep recurrent convolutional neural network for remaining useful life prediction
Remaining Useful Life (RUL) prediction of rotating machinery plays a critical role in
Prognostics and Health Management (PHM). Data-driven methods for RUL estimation have …
Prognostics and Health Management (PHM). Data-driven methods for RUL estimation have …
Tailings pond risk prediction using long short-term memory networks
J Li, H Chen, T Zhou, X Li - IEEE Access, 2019 - ieeexplore.ieee.org
Tailings ponds are a major hazard, and are ranked 18th in the risk assessment of world
accident hazards. The saturation line height is one of the most important factors that affects …
accident hazards. The saturation line height is one of the most important factors that affects …
An improved PF remaining useful life prediction method based on quantum genetics and LSTM
Y Ge, L Sun, J Ma - IEEE Access, 2019 - ieeexplore.ieee.org
Remaining useful life (RUL) is the premise and basis of the equipment health management
plan. As accurate as possible life prediction is of great significance to reliability and …
plan. As accurate as possible life prediction is of great significance to reliability and …
Remaining useful life prediction for nonlinear degraded equipment with bivariate time scales
As the fundamental and prerequisite work of remaining useful life (RUL) prediction,
degradation modeling directly affects the accuracy of RUL prediction. Existing degradation …
degradation modeling directly affects the accuracy of RUL prediction. Existing degradation …
An improved LSTM neural network with uncertainty to predict remaining useful life
R Wu, J Ma - 2019 CAA Symposium on Fault Detection …, 2019 - ieeexplore.ieee.org
Data-driven Prognostic (DDP) has become one of the major method of component of
prognostic and healthy management (PHM) systems in the industrial area. The fault …
prognostic and healthy management (PHM) systems in the industrial area. The fault …