Results 1 to 10 of about 16,926 (152)

A Prediction Method for the RUL of Equipment for Missing Data [PDF]

Complexity, 2021
We present a prediction framework to estimate the remaining useful life (RUL) of equipment based on the generative adversarial imputation net (GAIN) and multiscale deep convolutional neural network and long short‐term memory (MSDCNN‐LSTM). The method we proposed addresses the problem of missing data caused by sensor failures in engineering applications.
Wenbai Chen, Chang Liu 0120, Weizhao Chen, Huixiang Liu, Qili Chen, Peiliang Wu   +5 more
openaire   +2 more sources

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

Shapelet selection based on a genetic algorithm for remaining useful life prediction with supervised learning

Heliyon, 2022
RUL (remaining useful life) shapelets were recently developed to overcome the shortcomings of similarity-based RUL prediction methods, such as high sensitivity to parameters.
Gilseung Ahn, Min-Ki Jin, Seok-Beom Hwang, Sun Hur   +3 more
doaj   +1 more source

Uncertainty-Controlled Remaining Useful Life Prediction of Bearings with a New Data-Augmentation Strategy

Applied Sciences, 2022
The remaining useful life (RUL) of bearings based on deep learning methods has been increasingly used. However, there are still two obstacles in deep learning RUL prediction: (1) the training process of the deep learning model requires enough data, but ...
Ran Wang, Fucheng Yan, Ruyu Shi, Liang Yu, Yingjun Deng   +4 more
doaj   +1 more source

LSTM-Based Multi-Task Method for Remaining Useful Life Prediction under Corrupted Sensor Data

Machines, 2023
Data-driven remaining useful life (RUL) prediction plays a vital role in modern industries. However, unpredictable corruption may occur in the collected sensor data due to various disturbances in the real industrial conditions.
Kai Zhang, Ruonan Liu
doaj   +1 more source

XGBoost-Based Remaining Useful Life Estimation Model with Extended Kalman Particle Filter for Lithium-Ion Batteries

Sensors, 2022
The instability and variable lifetime are the benefits of high efficiency and low-cost issues in lithium-ion batteries.An accurate equipment’s remaining useful life prediction is essential for successful requirement-based maintenance to improve ...
Sadiqa Jafari, Yung-Cheol Byun
doaj   +1 more source

Remaining Useful Life Prediction of Bearings Based on Convolution Attention Mechanism and Temporal Convolution Network

IEEE Access, 2023
The prediction of the remaining useful life (RUL) of bearings is of great significance for reducing cost and increasing efficiency of mechanical equipment and ensuring healthy operation.
Haitao Wang, Jie Yang, Ruihua Wang, Lichen Shi   +3 more
doaj   +1 more source

A Novel Remaining Useful Life Prediction Method Based on CEEMDAN-IFTC-PSR and Ensemble CNN/BiLSTM Model for Cutting Tool

IEEE Access, 2022
To accurately predict the remaining useful life (RUL) of cutting tool, a novel RUL prediction method is proposed. Firstly, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used to decompose original cutting tool ...
Lanjun Wan, Keyu Chen, Yuanyuan Li, Yuezhong Wu, Zhibing Wang, Changyun Li   +5 more
doaj   +1 more source

Optimal Maintenance Decision Based on Remaining Useful Lifetime Prediction for the Equipment Subject to Imperfect Maintenance

IEEE Access, 2020
Focusing on the fact that the existing research on optimal maintenance decision for remaining useful lifetime (RUL) prediction and imperfect maintenance has low accuracy of RUL prediction and rationality of decision results, an optimal maintenance ...
Yunxiang Chen, Zezhou Wang, Zhongyi Cai
doaj   +1 more source

Smooth particle filter‐based likelihood approximations for remaining useful life prediction of Lithium‐ion batteries

IET Smart Grid, 2021
Accurate prediction of the remaining useful life (RUL) in Lithium‐ion batteries (LiBs) is a key aspect of managing its health, in order to promote reliable and secure systems, and to reduce the need for unscheduled maintenance and costs.
Mo'ath El‐Dalahmeh, Maher Al‐Greer, Ma'd El‐Dalahmeh, Michael Short   +3 more
doaj   +1 more source