Results 31 to 40 of about 9,187,359 (195)

A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification

Sensors
Remaining Useful Life (RUL) prediction is a crucial task in predictive maintenance. Currently, gated recurrent networks, hybrid models, and attention-enhanced models used for predictive maintenance face the challenge of balancing prediction accuracy and ...
Lilu Wang, Yongqi Li, Haiyuan Liu, Taihui Liu   +3 more
doaj   +1 more source

Remaining useful life prediction of rotating equipment using covariate-based hazard models : Industry applications [PDF]

, 2017
The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime
Yarlagadda, Prasad K., Mittinty, Murthy, Yarlagadda, Prasad, Gorjian, Nima, Sun, Yong, Ma, Lin   +5 more
core   +2 more sources

Remaining Useful Life Estimation Framework for the Main Bearing of Wind Turbines Operating in Real Time

Energies
The prognosis of wind turbine failures in real operating conditions is a significant gap in the academic literature and is essential for achieving viable performance parameters for the operation and maintenance of these machines, especially those located
Januário Leal de Moraes Vieira, Felipe Costa Farias, Alvaro Antonio Villa Ochoa, Frederico Duarte de Menezes, Alexandre Carlos Araújo da Costa, José Ângelo Peixoto da Costa, Gustavo de Novaes Pires Leite, Olga de Castro Vilela, Marrison Gabriel Guedes de Souza, Paula Suemy Arruda Michima   +9 more
doaj   +1 more source

Long Short-Term Memory Neural Network with Transfer Learning and Ensemble Learning for Remaining Useful Life Prediction

Sensors, 2022
Prediction of remaining useful life (RUL) is greatly significant for improving the safety and reliability of manufacturing equipment. However, in real industry, it is difficult for RUL prediction models trained on a small sample of faults to obtain ...
Lixiong Wang, Hanjie Liu, Zhen Pan, Dian Fan, Ciming Zhou, Zhigang Wang   +5 more
doaj   +1 more source

Development of a remaining useful life (RUL) model for reinforced concrete beams subjected to high-cycle fatigue [PDF]

, 2022
PURPOSE : Failure of a critical reinforced concrete beam due to fatigue can have severe safety and production consequences, and preventative repair/replacement of such a beam is expensive.
Inglis, Helen Mary, Wannenburg, Willem, Wannenburg, Johann, Roth, C.P. (Chris)   +3 more
core   +1 more source

Tracking Battery Microstructural Degradation Through Directional Thermal Transport Signatures

Advanced Functional Materials, EarlyView.
In lithium‐ion batteries, heat conduction varies between the through‐plane and in‐plane directions because of the cell's layered structure. Therefore, cell degradation influences thermal conductivity in each direction uniquely due to detailed microstructural and compositional changes.
Mohammad Shoghi Tekmedash, Rituparna Mohanty, Jack Leber, David Nageb, Mirella Richard, Sharan Singh, Amin Reihani   +6 more
wiley   +1 more source

A data-driven framework for remaining useful life estimation [PDF]

, 2017
Remaining useful life (RUL) estimation is one of the most common tasks in the field of prognostics and structural health management. The aim of this research is to estimate the remaining useful life of an unspecified complex system using some data-driven
Nguyen, Hoa Dinh
core   +2 more sources

Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox

Energies, 2016
Predicting the remaining useful life (RUL) of critical subassemblies can provide an advanced maintenance strategy for wind turbines installed in remote regions.
Wei Teng, Xiaolong Zhang, Yibing Liu, Andrew Kusiak, Zhiyong Ma   +4 more
doaj   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Remaining useful life prognosis of turbofan engines based on deep feature extraction and fusion

Scientific Reports, 2022
In turbofan engine datasets, to address problems, such as noise interference, diverse data types, large data volumes, complex feature extraction, inability to effectively describe degradation trends, and poor remaining useful life (RUL) prognosis effects,
Cheng Peng, Yufeng Chen, Weihua Gui, Zhaohui Tang, Changyun Li   +4 more
doaj   +1 more source