Results 101 to 110 of about 10,974,174 (198)

Remaining useful life prediction for ball bearings based on health indicators

, 2018
International audienceUncertainty in remaining useful life (RUL) prediction is nowadays a scientific problem that occupies industrials. Many prognostic models have been developed to respond to this issue from probabilistic to non-probabilistic approaches.
Zerhouni, Noureddine, Varnier, Christophe, Schaible, Patrick, Al Masry, Zeina   +3 more
core  

Prediction of Remaining Useful Life (RUL) in Refinery using Deep Learning

, 2019
The Remaining Useful Life (RUL) is typically used as the process of predicting the life span of machine before its failure. The purpose of this project is to develop a predictive analysis system of Remaining Useful Life (RUL) in refinery.
Baharadin, Hazirah
core  

Remaining Life Prediction of Bearings Based on Improved IF-SCINet

IEEE Access
In the field of health management, predicting the remaining useful life (RUL) of a device becomes critical. However, the RUL prediction process is often affected by a various of confounding factors, resulting in reduced prediction accuracy.
Jing Zhang, Chao Zhang, Shuai Xu, Guiyi Liu, Hongbo Fei, Le Wu   +5 more
doaj   +1 more source

A NEW PREDICTION METHOD FOR RUL PREDICTION OF CRUSHER ROLL IN NON STATIONARY PARTIALLY OBSERVED STATE

Jixie qiangdu, 2018
Accurate prediction of the remaining useful life（RUL） of the roller with double toothed roll crusher is an important basis for maintenance personnel to make scientific maintenance decision.
WU JianJun, LIU HaiPing, YE Xiang
doaj  

FOG COMPUTING BASED BEARING REMAINING USEFUL LIFE PROGNOSIS USING TIME SERIES NORMALIZED SIMILARITY AND RECURRENT NEURAL NETWORKS [PDF]

, 2019
Techniques are described for determining a remaining useful life (RUL) prognosis of bearings using a feature extraction module for extracting time series normalized similarity (TSNS) features for vibration data normalization and a prediction module ...
Jiao, Cheng, Liu, Tonny
core  

Remaining Useful Life Prediction for Aircraft Engines using LSTM

This study uses a Long Short-Term Memory (LSTM) network to predict the remaining useful life (RUL) of jet engines from time-series data, crucial for aircraft maintenance and safety.
Mohiuddin, Mohammed Basheer, Peringal, Anees, Hassan, Ahmed   +2 more
core  

Attentive Bidirectional Long Short-Term Memory Model to Predict the Remaining Useful Life of Aircraft Engines

Accurate Remaining Useful Life (RUL) prediction for turbofan engines remains a challenging issue for the aviation industry due to operational condition variability, sensor noise, and the relatively complex degradation patterns of turbofans.
Deo, Ravinesh C., Seixas Leal, Andreia, Ali, Mumtaz, Prasad, Salvin Sanjesh, Berton, Lilian, De Castro Santos, Luis Carlos   +5 more
core   +1 more source

AI-driven lithium-ion battery health prediction: a review of SOC, SOH and RUL estimation techniques. [PDF]

Front Artif Intell
Tamizharasi G, Rajini GK.
europepmc   +1 more source

A survey on few-shot learning for remaining useful life prediction

The prediction performance of most data-driven remaining useful life (RUL) prediction methods relies on sufficient training samples, which is challenging in few-shot scenarios such as time-consuming or expensive monitoring, and the lack of historical ...
Zhou, Han, Si, Xiaosheng, Mo, Renpeng, Yin, Hongpeng   +3 more
core   +2 more sources

Mechanism-Informed Health Representation and Causal Stage-Aware Remaining Useful Life Prediction for Rolling Bearings. [PDF]

Sensors (Basel)
Tian X, Yin H, Chen S, Dong Z, Xu H.
europepmc   +1 more source