Results 291 to 300 of about 8,942,242 (366)

Spatio-Temporal Fusion Attention: A Novel Approach for Remaining Useful Life Prediction Based on Graph Neural Network

IEEE Transactions on Instrumentation and Measurement, 2022
Prognostics and health management applications rely heavily on predicting industrial equipment’s remaining useful life (RUL). The traditional RUL prediction approaches mainly consider the nonlinear mapping relationship of time series data but rarely ...
Ziqian Kong, Xiaohang Jin, Zhengguo Xu, Bin Zhang   +3 more
semanticscholar   +1 more source

Remaining Useful Life Prediction Using a Novel Feature-Attention-Based End-to-End Approach

IEEE Transactions on Industrial Informatics, 2021
Deep learning plays an increasingly important role in industrial applications, such as the remaining useful life (RUL) prediction of machines. However, when dealing with multifeature data, most deep learning approaches do not have effective mechanisms to
Hui Liu, Zhen-yu Liu, Weiqiang Jia, Xianke Lin   +3 more
semanticscholar   +1 more source

Life Prediction of Notched Components

Journal of Engineering Materials and Technology, 1995
In this study, keyhole and smooth specimens, made from a low alloy pressure vessel steel (ASTM A-533 grade B), were subjected to monoaxial fatigue tests. The results show the influence of the stress concentration factor, Kt, on the number of cycles to failure, Nf.
GIGLIO, MARCO, VERGANI, LAURA MARIA
openaire   +2 more sources

Li-Ion Battery State of Health Estimation and Remaining Useful Life Prediction Through a Model-Data-Fusion Method

IEEE transactions on power electronics, 2021
The prognostics and health management of Li-ion batteries in electric vehicles are challenging due to the time-varying and nonlinear battery degradation.
Zhiqiang Lyu, Renjing Gao, Lin Chen
semanticscholar   +1 more source

A Novel Transfer Learning Approach in Remaining Useful Life Prediction for Incomplete Dataset

IEEE Transactions on Instrumentation and Measurement, 2022
Due to the successful implementation of intelligent data-driven approaches, these methods are gaining remarkable attention in predicting the remaining useful life (RUL) problems.
Shahin Siahpour, Xiang Li, J. Lee
semanticscholar   +1 more source

A Data-Model Interactive Remaining Useful Life Prediction Approach of Lithium-Ion Batteries Based on PF-BiGRU-TSAM

IEEE Transactions on Industrial Informatics
Accurate remaining useful life (RUL) prediction of lithium-ion batteries is critical for energy supply systems. In conventional data-driven RUL prediction approaches, the battery's degradation mechanism is difficult into incorporate in the RUL prediction.
Jiusi Zhang, Congsheng Huang, Mo-Yuen Chow, Xiang Li, Jilun Tian, Hao Luo, Shen Yin   +6 more
semanticscholar   +1 more source

Partial Domain Adaptation in Remaining Useful Life Prediction With Incomplete Target Data

IEEE/ASME transactions on mechatronics
Intelligent machinery prognostics and health management (PHM) methods have been attracting growing attention in the past years, with the rapid development of the artificial intelligence algorithms.
Xiang Li, Wei Zhang, Xu Li, Hongshen Hao
semanticscholar   +1 more source

Domain Adaptive Remaining Useful Life Prediction With Transformer

IEEE Transactions on Instrumentation and Measurement, 2022
Prognostic health management (PHM) has become a crucial part in building highly automated systems, whose primary task is to precisely predict the remaining useful life (RUL) of the system. Recently, deep models including convolutional neural network (CNN)
Xinyao Li, Jingjing Li, Lin Zuo, Lei Zhu, H. Shen   +4 more
semanticscholar   +1 more source

Life Cycle Assessment and Service Life Prediction

Journal of Industrial Ecology, 2014
SummaryModels of buildings in life cycle assessment (LCA) often use simple descriptions of operational energy, maintenance, and material replacement. The scope of many building LCAs is often limited and uses assumptions such as building lifetimes of 30 to 50 years.
Aneurin Grant, Robert Ries, Charles Kibert   +2 more
openaire   +1 more source

Transfer Learning-Based Hybrid Remaining Useful Life Prediction for Lithium-Ion Batteries Under Different Stresses

IEEE Transactions on Instrumentation and Measurement, 2022
Accurate remaining useful life (RUL) prediction of lithium-ion battery is very important for the safety of power system of mobile equipment. At present, most of the currently proposed RUL prediction methods for lithium-ion batteries are limited by the ...
Dawei Pan, Hengfeng Li, Shaojun Wang
semanticscholar   +1 more source