Results 51 to 60 of about 11,323,207 (336)

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

, 2015
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, Murthy Mittinty, Mittinty, M., Nima Gorjian, Lin Ma, Yong Sun, Gorjian, N., Prasad Yarlagadda, Ma, L., Sun, Y., Yarlagadda, P.   +15 more
core   +2 more sources

Transformer Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

IEEE Access, 2022
Accurately predicting the Remaining Useful Life (RUL) of a Li-ion battery plays an important role in managing the health and estimating the state of a battery.
Daoquan Chen, Weicong Hong, Xiuze Zhou
doaj   +1 more source

Battery Health Monitoring and Remaining Useful Life Prediction Techniques: A Review of Technologies

Batteries
Lithium-ion (Li-ion) batteries have become essential in modern industries and domestic applications due to their high energy density and efficiency.
Mohamed Ahwiadi, Wilson Wang
semanticscholar   +1 more source

Predicting the Remaining Useful Life of Supercapacitors under Different Operating Conditions

Energies
With the rapid development of the new energy industry, supercapacitors have become key devices in the field of energy storage. To forecast the remaining useful life (RUL) of supercapacitors, we introduce a new technology that integrates variational mode ...
Guangheng Qi, Ning Ma, Kai Wang
doaj   +1 more source

Remaining useful life prediction based on an integrated neural network

工程科学学报, 2020
Unexpected failures and unscheduled maintenance activities of mechanical systems might incur considerable waste of resources and high investment costs. Thus, in recent years, prognostics and health management (PHM) has received a lot of attention because
Yong-feng ZHANG, Zhi-qiang LU
doaj   +1 more source

Remaining Useful Life Prediction of a Turbofan Engine Using Deep Layer Recurrent Neural Networks [PDF]

, 2021
Turbofan engine is a pivotal component of the aircraft. Engine components are susceptible to degradation over the life of their operation which affects the performance of an engine.
Thakkar, Unnati Rajeshkumar
core   +1 more source

Data-Driven Machine Learning Methods for Remaining Useful Life Prediction

, 2022
I will present my work exploring machine learning solutions for remaining useful life prediction for physical devices. In my work, I predict remaining useful life for hard-disk drives and aircraft engines.
Coursey, Austin
core   +1 more source

Remaining Useful Life Prediction of Lithium-Ion Battery Using ICC-CNN-LSTM Methodology

Energies, 2023
In recent years, lithium-ion batteries have gained significant attention due to their crucial role in various applications, such as electric vehicles and renewable energy storage.
Catherine Rincón-Maya, Fernando Guevara-Carazas, Freddy Hernández-Barajas, Carmen Patino-Rodriguez, Olga Usuga-Manco   +4 more
doaj   +1 more source

A hybrid approach for lithium-ion battery remaining useful life prediction using signal decomposition and machine learning

Scientific Reports
Lithium-ion batteries are widely used in many fields, and accurate prediction of their remaining useful life (RUL) was crucial for effective battery management and safety assurance.
Yi-Biao Fan, Zhi-Shan Lin, Fan Wang, Jianpeng Zhang   +3 more
semanticscholar   +1 more source

Comparative Drug Response Profiling in Neuroblastoma Cell Lines and Patient‐Derived Tumor Organoids

Pediatric Blood &Cancer, EarlyView.
ABSTRACT High‐risk neuroblastoma remains a leading cause of pediatric cancer mortality, and improved preclinical models are needed to guide therapeutic developments. We screened seven high‐risk neuroblastoma cell lines and three patient‐derived tumor organoids with 528 compounds alongside bone marrow controls, and compared them with external datasets ...
Krzysztof Wierbiłowicz, Se Whee Sammy Park, Aironas Los, Ernest Liu, Nona Struyf, Tom Erkers, Sören Lehmann, Jan J. Molenaar, Jakob Stenman, Olli Kallioniemi, Päivi Östling, Brinton Seashore‐Ludlow, Kasper Karlsson   +12 more
wiley   +1 more source