Results 61 to 70 of about 1,643,808 (218)

Weibull Variational Autoencoder for Remaining Useful Life Prediction

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Remaining useful life (RUL) prediction is a critical technology for preventing unexpected failures and reducing maintenance costs in modern industrial systems. However, traditional model‐based approaches are limited by the need for explicit mathematical modeling of degradation mechanisms, while data‐driven methods often require large‐scale ...
JunWoo Yu, Yoojin Jang, Kwanghui Shin, Jinsoo Jeong, Yong Soo Kim   +4 more
wiley   +1 more source

Data-Driven Remaining Useful Life Prediction Considering Sensor Anomaly Detection and Data Recovery

IEEE Access, 2019
Prognostics and health management (PHM) is being adopted more and more in the modern engineering systems. As one of the most important technologies in the PHM domain, remaining useful life (RUL) prediction has attracted much attention from the ...
Liansheng Liu, Qing Guo, Datong Liu, Yu Peng   +3 more
doaj   +1 more source

Remaining useful life prediction method of EV power battery for DC fast charging condition

Energy Reports, 2022
To realize the online rapid prediction of the remaining useful life (RUL) of electric vehicle (EV) power battery under direct current (DC) fast charging conditions and reduce the influence of complex health indicator (HI) on the prediction accuracy, an ...
Shaotang Cai, Jun Hu, Shuoqi Ma, Zhenning Yang, Hao Wu   +4 more
doaj   +1 more source

Portfolio‐Level Reliability Analysis of a Multi‐Asset System: A Frailty Proportional Intensity Modeling Framework

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Understanding and modeling the equipment failure behavior is crucial for reducing downtime, optimizing maintenance strategies, and improving operational safety. This challenge becomes particularly critical in industrial contexts involving multi‐asset portfolios, where heterogeneous conditions influence the reliability of individual assets and,
Zeynab Allahkarami, Ahmad Reza Sayadi, Behzad Ghodrati, Ebru Turanoglu Bekar, Anders Skoogh   +4 more
wiley   +1 more source

Aircraft Engines Remaining Useful Life Prediction Based on A Hybrid Model of Autoencoder and Deep Belief Network

IEEE Access, 2022
Remaining Useful Life (RUL) is used to provide an early indication of failures that required performing maintenance and/or replacement of the system in advance.
Huthaifa Al-Khazraji, Ahmed R. Nasser, Ahmed M. Hasan, Ammar K. Al Mhdawi, Hamed Al-Raweshidy, Amjad J. Humaidi   +5 more
doaj   +1 more source

Empirical Physics‐Based Normal Behavior Modeling of Drive Train Temperatures With High‐Resolution Wind Turbine Operating Data

Wind Energy, EarlyView.
ABSTRACT The installed wind energy capacity increases every year. However, operation and maintenance costs still make up a considerable portion of the levelized costs of electricity. This costs can be greatly reduced by the application of suitable early fault detection methods. The supervisory control and data acquisition system of wind turbines is one
Timo Lichtenstein, Victor von Maltzahn, Karoline Pelka   +2 more
wiley   +1 more source

Digital Twin and Data-Driven Remaining Useful Life Prediction of Gearbox

IEEE Access
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

NanoSentry: An Edge‐Deployable Unified Neural Architecture for Multi‐Domain Industrial Prognostics and Health Management

Artificial Intelligence for Engineering, EarlyView.
NanoSentry, a sub‐50 KiB unified architecture for multi‐domain prognostics, matches or outperforms models 4.5× $4.5\times $ larger across turbofan, battery, and bearing benchmarks while reducing end‐of‐life prediction error up to 5.8× $5.8\times $. Physical STM32H7 deployment confirms sub‐3 ms inference and up to 26 KiB peak SRAM without quantisation ...
Naem Azam Chowdhury, Abu Nasek, Khan Prottoy, Md Hamid Borkot Tulla, Jafor Sadik Chowdhury   +4 more
wiley   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng   +4 more
wiley   +1 more source

RUL Prediction for Lithium Batteries Using a Novel Ensemble Learning Method

, 2022
The remaining useful life (RUL) is the key element of fault diagnosis, prediction and health management (PHM) during the equipment operation service period.
Linggang Kong, Zheng Cheng, Yonghui Yang, Hongfu Zuo, Jiaju Wu   +4 more
core   +1 more source