Results 221 to 230 of about 530,506 (256)

Remaining Useful Life Prediction Based on Spatiotemporal Autoencoder

SSRN Electronic Journal, 2022
Tao Xu, Dechang Pi, Shi Zeng
openaire   +1 more source

The Study of Hyperparameters in the Prediction of Remaining Useful Life

Volume 11: Safety Engineering, Risk and Reliability Analysis; Research Posters
Abstract Despite the extensive body of literature on RUL prediction techniques, there is still a need to understand how hyperparameters affect these predictions’ error and aleatoric and epistemic uncertainty. Motivated by this need, the research question was: Does applying machine learning architecture enhance uncertainty quantification ...
Nazir Laureano Gandur, Stephen Ekwaro-Osire   +1 more
openaire   +1 more source

Predicting Remaining Useful Life of Well Tubulars

Ibero-Latin American Congress on Computational Methods in Engineering (CILAMCE)
This work proposes a reliability-based framework to estimate the Remaining Useful Life (RUL) of well tubulars throughout the lifecycle of oil and gas wells. The RUL estimation is supported by a probabilistic analysis that accounts for uncertainties in geometrical and material properties, based on failure modes defined in the API/TR 5C3 standard.
null Luís Philipe Ribeiro Almeida, null Lucas Gouveia, null Thiago Barbosa, null Eduardo Toledo Lima Junior, null João Paulo Lima Santos, null Danilo Colombo, null Andre Luis Severino Abrego   +6 more
openaire   +1 more source

Remaining Useful Life Prediction of Equipment Based on XGBoost

Proceedings of the 5th International Conference on Computer Science and Application Engineering, 2021
Zhiyang Jia, Zhibo Xiao, Yijin Shi
openaire   +1 more source

Domain Adaptive Remaining Useful Life Prediction With Transformer

IEEE Transactions on Instrumentation and Measurement, 2022
Xinyao Li, Jingjing Li 0001, Lin Zuo, Lei Zhu 0002, Heng Tao Shen   +4 more
openaire   +1 more source

Remaining useful life prediction of bearing based on stacked autoencoder and recurrent neural network

Journal of Manufacturing Systems, 2021
Tian Han, Jiachen Pang
exaly  

Predicting Remaining Useful Life Using AdaBoost Algorithm

Advances in Science and Technology
Predicting the Remaining Useful Life (RUL) of machinery and critical components is crucial for proactive maintenance and operational efficiency in industrial settings. This paper presents an approach to RUL prediction using the AdaBoost algorithm, a technique that iteratively improves prediction accuracy by focusing on difficult-to-predict cases.
openaire   +1 more source

Remaining Useful Life Prediction

2023
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A critical review of improved deep learning methods for the remaining useful life prediction of lithium-ion batteries

Energy Reports, 2021
Shunli Wang, Siyu Jin, Haotian Shi
exaly  

A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings

Reliability Engineering and System Safety, 2021
Yudong Cao, Yifei Ding, Minping Jia
exaly