Results 61 to 70 of about 9,948,079 (293)
Remaining useful life prediction of rotating equipment using covariate-based hazard models : Industry applications [PDF]
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. +15 more
core +2 more sources
Predicting the Remaining Useful Life of Supercapacitors under Different Operating Conditions
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
Deep Spatiotemporal Convolutional-Neural-Network-Based Remaining Useful Life Estimation of Bearings
The remaining useful life (RUL) estimation of bearings is critical for ensuring the reliability of mechanical systems. Owing to the rapid development of deep learning methods, a multitude of data-driven RUL estimation approaches have been proposed ...
Xu Wang +6 more
doaj +1 more source
ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo +5 more
wiley +1 more source
A semi-supervised approach with monotonic constraints for improved remaining useful life estimation [PDF]
Remaining useful life is of great value in the industry and is a key component of Prognostics and Health Management (PHM) in the context of the Predictive Maintenance (PdM) strategy.
Ompusunggu, Agusmian Partogi +14 more
core +1 more source
Digital Twin and Data-Driven Remaining Useful Life Prediction of Gearbox
Traditional approaches for predicting the remaining useful life (RUL) of gearboxes often face challenges in integrating physical and virtual data, leading to reduced prediction accuracy and an increased risk of system failure.
Quanbo Lu, Mei Li, Xiaojuan Huang
doaj +1 more source
ABSTRACT Introduction This final analysis of a multicenter, prospective postmarketing surveillance study evaluated the safety of daprodustat in patients with chronic kidney disease anemia in routine clinical practice in Japan. Methods Patients who initiated daprodustat between September 2020 and July 2022 were registered.
Tadao Akizawa +7 more
wiley +1 more source
Data-Driven Machine Learning Methods for Remaining Useful Life Prediction
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
An Explainable Artificial Intelligence Approach for Remaining Useful Life Prediction
Prognosis and health management depend on sufficient prior knowledge of the degradation process of critical components to predict the remaining useful life. This task is composed of two phases: learning and prediction.
Genane Youness, Adam Aalah
doaj +1 more source

