Results 21 to 30 of about 10,974,174 (198)

Research on Remaining Useful Life Prognostics Based on Fuzzy Evaluation-Gaussian Process Regression Method

IEEE Access, 2020
To achieve efficient and accurate remaining life prediction and effectively express the uncertainty of prediction results, this paper proposes a remaining life prediction method based on fuzzy evaluation-Gaussian process regression (FE-GPR).
Weijie Kang, Jiyang Xiao, Mingqing Xiao, Yangguang Hu, Haizhen Zhu, Jianfeng Li   +5 more
doaj   +1 more source

Lithium-ion battery remaining useful life prediction [PDF]

, 2021
Lithium-Ion Battery Remaining Useful Life Prediction work consists of an initial approach to battery life prediction using Severson dataset and data-driven LSTM-based RUL predictive methods. Although the memory is written in English, the presentation
Larrarte Lizarralde, Beñat
core   +2 more sources

Review on State Estimation and Remaining Useful Life Prediction Methods for Lithium-ion Battery

发电技术, 2023
Accurate estimation of state of charge (SOC), battery state of health (SOH) and prediction of battery remaining useful life (RUL) of lithium-ion battery are important contents of battery management. It is of great significance to prolong battery life and
ZHAO Jiahui, TIAN Liting, CHENG Lin
doaj   +1 more source

A Novel Approach of Label Construction for Predicting Remaining Useful Life of Machinery

Shock and Vibration, 2021
Rolling bearings are key components of rotating machinery, and predicting the remaining useful life (RUL) is of great significance in practical industrial scenarios and is being increasingly studied.
Hailong Lin, Zihao Lei, Guangrui Wen, Xiaojun Tian, Xin Huang, Jinsong Liu, Haoxuan Zhou, Xuefeng Chen   +7 more
doaj   +1 more source

jiaxiang-cheng/transformer-pytorch-remaining-useful-life-prediction: Pre-release with Minimum Implementation

, 2021
Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021).
Jia-Xiang Cheng
core   +1 more source

A Framework for Predicting Remaining Useful Life Curve of Rolling Bearings Under Defect Progression Based on Neural Network and Bayesian Method

IEEE Access, 2021
In order to improve Remaining Useful Life (RUL) prediction accuracy for rolling bearings under defect progressing, the robustness for individual differences and the fluctuation of vibration features are challenging issues.
Masashi Kitai, Takuji Kobayashi, Hiroki Fujiwara, Ryoji Tani, Masayuki Numao, Ken-Ichi Fukui   +5 more
doaj   +1 more source

Machine performance degradation assessment and remaining useful life prediction using proportional hazard model and support vector machine [PDF]

, 2012
Machine performance degradation assessment and remaining useful life (RUL) prediction are of crucial importance in condition-based maintenance to reduce the maintenance cost and improve the reliability.
Yang, Bo-Suk, Tran, Van Tung, Pham, Hong Thom, Nguyen, Tan Tien   +3 more
core   +1 more source

Residual Remaining Useful Life Prediction Method for Lithium-Ion Batteries in Satellite With Incomplete Healthy Historical Data

IEEE Access, 2019
Due to the strict requirements of satellite systems, accurate remaining useful life (RUL) prediction of the key components is very important to the reliability and security of satellite systems.
Jian Peng, Zhongbao Zhou, Jiongqi Wang, Di Wu, Yinman Guo   +4 more
doaj   +1 more source

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

jiaxiang-cheng/cnn-pytorch-remaining-useful-life-prediction: RUL Prediction with CNN

, 2021
Inspired by Babu, G. S., Zhao, P., & Li, X. L. (2016, April). Deep convolutional neural network-based regression approach for estimation of remaining useful life. In International conference on database systems for advanced applications (pp.
Jia-Xiang Cheng
core   +1 more source