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 +10 more sources
A hybrid CNN-DNN model for battery remaining useful life RUL prediction [PDF]
Scientific ReportsAccurate prediction of the Remaining Useful Life of lithium-ion batteries is essential for enhancing reliability, safety, and maintenance planning in energy storage systems.
Hala Khoufi +3 more
doaj +3 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 +4 more sources
Ensemble Neural Networks for Remaining Useful Life (RUL) Prediction [PDF]
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). Most of the current data-driven approaches for RUL prediction focus on single-point prediction.
Abhishek Srinivasan +2 more
openaire +3 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 +2 more sources
Mar-RUL: A remaining useful life prediction approach for fault prognostics of marine machinery [PDF]
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.
Velasco-Gallego, Christian +1 more
core +6 more sources
A two-stage framework for cost-sensitive predictive maintenance using deep learning, GANs, and risk-aware clustering [PDF]
Scientific ReportsPredictive maintenance (PdM) has seen significant advances through machine learning, yet its practical deployment remains challenged by data scarcity, system complexity, and uncertainty in cost-related decisions.
Ali Hakami
doaj +2 more sources
Prediction of Remaining Useful Life (RUL) of Lithium ion (Li-ion) Batteries [PDF]
, 2020 In recent time Li-ion battery gained popularity because of their high charge density, portability and longer life span. It compliments the human quest for green energy. As many of the green energy applications like Electrical Vehicle, Wind Energy and Solar Energy use Li-ion battery as their energy storage device.
Shukla, Rashmikant T.
core +5 more sources
Remaining Useful Life Prediction for Lithium-Ion Battery: A Deep Learning Approach
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 +2 more sources
Prognostics for electronics components of avionics - NASA IGBT accelerated ageing case study [PDF]
, 2013 Insulate gate bipolar transistors (IGBTs) are widely used in electric vehicles, railway locomotive and new generation aircrafts, due to the IGBTs have advantages in small conduction resistance and small drive current.
Xie, Yuan'an
core +4 more sources