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 …
BiLSTM deep neural network model for imbalanced medical data of IoT systems
M Woźniak, M Wieczorek, J Siłka - Future Generation Computer Systems, 2023 - Elsevier
Health informatics is one of the most developed field in recent time. Computational
Intelligence is among the most influential factors that may help to improve patient oriented …
Intelligence is among the most influential factors that may help to improve patient oriented …
Aircraft engine run-to-failure dataset under real flight conditions for prognostics and diagnostics
A key enabler of intelligent maintenance systems is the ability to predict the remaining useful
lifetime (RUL) of its components, ie, prognostics. The development of data-driven …
lifetime (RUL) of its components, ie, prognostics. The development of data-driven …
[HTML][HTML] Human activity recognition based on residual network and BiLSTM
Y Li, L Wang - Sensors, 2022 - mdpi.com
Due to the wide application of human activity recognition (HAR) in sports and health, a large
number of HAR models based on deep learning have been proposed. However, many …
number of HAR models based on deep learning have been proposed. However, many …
A review of remaining useful life prediction approaches for mechanical equipment
Y Zhang, L Fang, Z Qi, H Deng - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
The precise maintenance and scientific management of large and complex mechanical
equipment are of great significance for ensuring the safe operation of equipment and …
equipment are of great significance for ensuring the safe operation of equipment and …
A real-time adaptive model for bearing fault classification and remaining useful life estimation using deep neural network
Rolling element bearings are essential components of a wide variety of industrial machinery
and the leading cause of equipment failure. The prediction of Remaining Useful Life (RUL) …
and the leading cause of equipment failure. The prediction of Remaining Useful Life (RUL) …
Automatic multi-differential deep learning and its application to machine remaining useful life prediction
Different levels of characteristic information cannot be mined using various feature extraction
modes in most neural networks, and thus, a novel method called the automatic multi …
modes in most neural networks, and thus, a novel method called the automatic multi …
Spatial-temporal dual-channel adaptive graph convolutional network for remaining useful life prediction with multi-sensor information fusion
X Zhang, Z Leng, Z Zhao, M Li, D Yu, X Chen - Advanced Engineering …, 2023 - Elsevier
Due to complex spatial correlations, dynamic temporal trends, and heterogeneities, accurate
remaining useful life (RUL) prediction is a challenging task for multi-sensor complex …
remaining useful life (RUL) prediction is a challenging task for multi-sensor complex …
Comprehensive machine and deep learning analysis of sensor-based human activity recognition
HM Balaha, AES Hassan - Neural Computing and Applications, 2023 - Springer
Abstract Human Activity Recognition (HAR) is a crucial research focus in the body area
networks and pervasive computing domains. The goal of HAR is to examine activities from …
networks and pervasive computing domains. The goal of HAR is to examine activities from …
Aircraft engines remaining useful life prediction based on a hybrid model of autoencoder and deep belief network
Remaining Useful Life (RUL) is used to provide an early indication of failures that required
performing maintenance and/or replacement of the system in advance. Accurate RUL …
performing maintenance and/or replacement of the system in advance. Accurate RUL …