A deep attention residual neural network-based remaining useful life prediction of machinery
F Zeng, Y Li, Y Jiang, G Song - Measurement, 2021 - Elsevier
Remaining useful life (RUL) estimation has always been an essential task of prognostics
health management (PHM). However, degradation data of machinery is seldom available …
health management (PHM). However, degradation data of machinery is seldom available …
Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery
Deep learning is becoming more appealing in remaining useful life (RUL) prediction of
machines, because it is able to automatically build the mapping relationship between the …
machines, because it is able to automatically build the mapping relationship between the …
Opelrul: Optimally weighted ensemble learner for remaining useful life prediction
Smart manufacturing utilizes a smart maintenance approach, constantly observing system
data to estimate machine failure. This smart maintenance, also known as predictive …
data to estimate machine failure. This smart maintenance, also known as predictive …
Data-Efficient Estimation of Remaining Useful Life for Machinery With a Limited Number of Run-to-Failure Training Sequences
G Sternharz, A Elhalwagy, T Kalganova - IEEE Access, 2022 - ieeexplore.ieee.org
Prognostics and Health Monitoring (PHM) of machinery is a research area with great
relevance to industrial applications as it can serve as a foundation for safer, more cost …
relevance to industrial applications as it can serve as a foundation for safer, more cost …
Remaining useful life (RUL) prediction of equipment in production lines using artificial neural networks
Z Kang, C Catal, B Tekinerdogan - Sensors, 2021 - mdpi.com
Predictive maintenance of production lines is important to early detect possible defects and
thus identify and apply the required maintenance activities to avoid possible breakdowns …
thus identify and apply the required maintenance activities to avoid possible breakdowns …
A new hybrid model for RUL prediction through machine learning
Remaining useful life (RUL) prediction plays a significant role in prognostics and health
management systems. While three different approaches have been utilized to estimate the …
management systems. While three different approaches have been utilized to estimate the …
Remaining useful life estimation for predictive maintenance using feature engineering
OE Yurek, D Birant - 2019 Innovations in intelligent systems …, 2019 - ieeexplore.ieee.org
Recently, machine learning techniques have been used to produce increasingly effective
solutions to predict the remaining useful life (RUL) of assets accurately. This paper …
solutions to predict the remaining useful life (RUL) of assets accurately. This paper …
Bayesian optimization LSTM/bi-LSTM network with self-optimized structure and hyperparameters for remaining useful life estimation of lathe spindle unit
An effective maintenance strategy to cut back maintenance costs and production loss with
assured product quality has always been a major concern for industries. The Industry 4.0 era …
assured product quality has always been a major concern for industries. The Industry 4.0 era …
[PDF][PDF] Survey on deep learning applied to predictive maintenance
Y Maher, B Danouj - Int. J. Electr. Comput. Eng, 2020 - academia.edu
Prognosis health monitoring (PHM) plays an increasingly important role in the management
of machines and manufactured products in today's industry, and deep learning plays an …
of machines and manufactured products in today's industry, and deep learning plays an …
Deep-learning-based remaining useful life prediction based on a multi-scale dilated convolution network
F Deng, Y Bi, Y Liu, S Yang - Mathematics, 2021 - mdpi.com
Remaining useful life (RUL) prediction of key components is an important influencing factor
in making accurate maintenance decisions for mechanical systems. With the rapid …
in making accurate maintenance decisions for mechanical systems. With the rapid …