Results 51 to 60 of about 11,244 (210)

Droplet microfluidics: Enabling the tailored fabrication of hydrogel particles

Droplet, EarlyView.
Droplet microfluidics enables precise, versatile fabrication of hydrogel particles with controlled size, composition, and structure. This review summarizes fundamental principles, engineering strategies, and emerging applications, providing a framework for advancing microfluidic hydrogel technologies.
Zhongqiao Gan, Xu Hou
wiley   +1 more source

Remaining Useful Life Prediction Method for Electric Submersible Pump System Based on DA-RNN

Shiyou jixie
Electric submersible pump （ESP） is the main artificial lift equipment in offshore oilfields. Its operation and maintenance costs are extremely high. Once it gets out of order， it will cause losses to oilfield operations.
Yu Jifei, Ji Yuchen, Lu Xin, Sui Xianfu, Peng Jianlin, Han Guoqing, Yang Yang   +6 more
doaj   +1 more source

Remaining Useful Life Prediction of High-Frequency Swing Self-Lubricating Liner

Shock and Vibration, 2021
The remaining useful life (RUL) prediction of self-lubricating spherical plain bearings is essential for replacement decision-making and the reliability of high-end equipment. The high-frequency swing self-lubricating liner (HSLL) is the key component of
Xiuhong Hao, Shuqiang Wang, Mengfan Chen, Deng Pan   +3 more
doaj   +1 more source

Particle Filter-Based Prognostics for an Electrolytic Capacitor Working in Variable Operating Conditions

, 2015
International audiencePrognostic models should properly take into account the effects of operating conditions on the degradation process and on the signal measurements used for monitoring.
Astigarraga, Daniel, Baraldi, Piero, Galarza, Ainhoa, Rigamonti, Marco, Zio, Enrico   +4 more
core   +4 more sources

A review of physics-based models in prognostics: application to gears and bearings of rotating machinery [PDF]

, 2016
Health condition monitoring for rotating machinery has been developed for many years due to its potential to reduce the cost of the maintenance operations and increase availability.
Cubillo, Adrian, Esperon Miguez, Manuel, Perinpanayagam, Suresh   +2 more
core   +2 more sources

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

Energy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom, Lotfi Saidi, Eric Bechhoefer   +2 more
wiley   +1 more source

A two-stage framework for cost-sensitive predictive maintenance using deep learning, GANs, and risk-aware clustering

Scientific Reports
Predictive 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   +1 more source

Lithium-ion batteries Remaining Useful Life Prediction Method Considering Recovery Phenomenon

International Journal of Electrochemical Science, 2019
Estimation of lithium battery remaining useful life (RUL) is the key to lithium battery health management. In the process of intermittent discharging lithium batteries, the recovery phenomenon will have a relatively large impact on the life of lithium ...
Zhenyu Zhang, Dongxu Shen, Zhen Peng, Yong Guan, Huimei Yuan, Lifeng Wu   +5 more
doaj   +1 more source

Predictive Maintenance of Manufacturing Industry Machines Using Remaining Useful Life (RUL) Prediction

International Journal of Computer Science and Mobile Computing
In this paper, a lightweight Autoencoder-LSTM is provided to predict Remaining Useful Life (RUL) of bearings in real-life circumstances with noisy sensors and a small amount of labeled information. The method involves unsupervised health indicator (HI) construction and time modelling that is supervised.
Vishwa Kiran K H, Mohan S H, Rohit M N, Divyashri C R   +3 more
openaire   +1 more source

Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations

Quality and Reliability Engineering International, EarlyView.
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim, Huadong Mo, Hemanshu Pota, Daoyi Dong   +3 more
wiley   +1 more source