Remaining Useful Life (RUL) Prediction of Equipment in Production Lines Using Artificial Neural Networks [PDF]
Sensors, 2021 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.
Ziqiu Kang +2 more
doaj +8 more sources
Remaining Useful Life Prediction for Lithium-Ion Battery: A Deep Learning Approach [PDF]
IEEE Access, 2018 Accurate prediction of remaining useful life (RUL) of lithium-ion battery plays an increasingly crucial role in the intelligent battery health management systems. The advances in deep learning introduce new data-driven approaches to this problem.
Lei Ren +5 more
doaj +5 more sources
Remaining Useful Life (RUL) Prediction Based on the Bivariant Two-Phase Nonlinear Wiener Degradation Process [PDF]
EntropyRecent advancements in science and technology have resulted in products with enhanced reliability and extended lifespans across the aerospace and related sectors.
Lijun Sun, Yuying Liang, Zaizai Yan
doaj +4 more sources
Ensemble Neural Networks for Remaining Useful Life (RUL) Prediction
PHM Society Asia-Pacific Conference, 2023 A core part of maintenance planning is a monitoring system that provides a good prognosis on health and degradation, often expressed as remaining useful life (RUL).
Andresen, Juan Carlos +2 more
core +2 more sources
Hybrid framework for Remaining Useful Life (RUL) prediction of rolling bearing faults
ArrayRemaining Useful Life (RUL) prediction is critical for preventing catastrophic failures in industrial systems, enabling efficient maintenance scheduling and resource optimization.
Ali Saeed +6 more
doaj +2 more sources
Mar-RUL: A remaining useful life prediction approach for fault prognostics of marine machinery
Applied Ocean Research, 2023 Although the maritime industry has the potential to lead smart maintenance methodologies, current maintenance routines within the sector focus on either reactive or preventive maintenance approaches; approaches which are increasingly conservative and often prompted by an increase of large costs or unnecessary maintenance actions.
Christian Velasco-Gallego +1 more
exaly +3 more sources
Research on Remaining Useful Life Prediction of Equipment Based on Digital Twins [PDF]
SensorsRemaining Useful Life (RUL) prediction is a key factor in fault diagnosis, prediction, and health management (PHM) during equipment operation and service.
Jiaju Wu +5 more
doaj +2 more sources
A Real-Time Diagnostic System Using a Long Short-Term Memory Model with Signal Reshaping Technology for Ship Propellers [PDF]
SensorsThis study develops a ship propeller diagnostic system to address the issue of insufficient ship maintenance capacity and enhance operational efficiency.
Sheng-Chih Shen +4 more
doaj +2 more sources
A Novel RUL-Centric Data Augmentation Method for Predicting the Remaining Useful Life of Bearings
MachinesMaintaining the reliability of rotating machinery in industrial environments entails significant challenges. The objective of this paper is to develop a methodology that can accurately predict the condition of rotating machinery in order to facilitate ...
Miao He, Zhonghua Li, Fangchao Hu
doaj +2 more sources
FDBRP: A Data–Model Co-Optimization Framework Towards Higher-Accuracy Bearing RUL Prediction [PDF]
SensorsThis paper proposes Feature fusion and Dilated causal convolution model for Bearing Remaining useful life Prediction (FDBRP), an integrated framework for accurate Remaining Useful Life (RUL) prediction of rolling bearings that combines three key ...
Muyu Lin +5 more
doaj +2 more sources