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

open access: yes
This paper proposes a three-stage method involved system identification techniques, proportional hazard model, and support vector machine for assessing the machine health degradation and forecasting the machine remaining useful life (RUL).
Tran, Van Tung
core   +3 more sources

Battery Remaining Useful Life Prediction with Inheritance Particle Filtering

open access: yesEnergies, 2019
Accurately forecasting a battery’s remaining useful life (RUL) plays an important role in the prognostics and health management of rechargeable batteries. An effective forecast is reported using a particle filter (PF), but it currently suffers from
Lin Li   +3 more
doaj   +1 more source

Remaining Useful Life Prediction Based on Multi-Representation Domain Adaptation

open access: yesMathematics, 2022
All current deep learning-based prediction methods for remaining useful life (RUL) assume that training and testing data have similar distributions, but the existence of various operating conditions, failure modes, and noise lead to insufficient data ...
Yi Lyu   +3 more
doaj   +1 more source

Remaining useful life prediction for equipment based on RF-BiLSTM

open access: yesAIP Advances, 2022
The prediction technology of remaining useful life has received a lot attention to ensure the reliability and stability of complex mechanical equipment. Due to the large-scale, non-linear, and high-dimensional characteristics of monitoring data, machine ...
Zhiqiang Wu   +8 more
doaj   +1 more source

Aero-Engine Remaining Useful Life Prediction Based on Bi-Discrepancy Network

open access: yesSensors, 2023
Most unsupervised domain adaptation (UDA) methods align feature distributions across different domains through adversarial learning. However, many of them require introducing an auxiliary domain alignment model, which incurs additional computational ...
Nachuan Liu   +3 more
doaj   +1 more source

Predicting Remaining Useful Life with Similarity-Based Priors [PDF]

open access: yes, 2020
Prognostics is the area of research that is concerned with predicting the remaining useful life of machines and machine parts. The remaining useful life is the time during which a machine or part can be used, before it must be replaced or repaired.
Youri Soons   +3 more
openaire   +3 more sources

LSTM-Based Broad Learning System for Remaining Useful Life Prediction

open access: yesMathematics, 2022
Prognostics and health management (PHM) are gradually being applied to production management processes as industrial production is gradually undergoing a transformation, turning into intelligent production and leading to increased demands on the ...
Xiaojia Wang   +3 more
doaj   +1 more source

Remaining Useful Life Prediction of High-Frequency Swing Self-Lubricating Liner

open access: yesShock and Vibration, 2021
The remaining useful life (RUL) prediction of self-lubricating spherical plain bearings is essential for replacement decision-making and the reliability of high-end equipment. The high-frequency swing self-lubricating liner (HSLL) is the key component of
Xiuhong Hao   +3 more
doaj   +1 more source

An Explainable Artificial Intelligence Approach for Remaining Useful Life Prediction

open access: yesAerospace, 2023
Prognosis and health management depend on sufficient prior knowledge of the degradation process of critical components to predict the remaining useful life. This task is composed of two phases: learning and prediction.
Genane Youness, Adam Aalah
doaj   +1 more source

Digital Twin-Driven Remaining Useful Life Prediction for Rolling Element Bearing

open access: yesMachines, 2023
Traditional methods for predicting remaining useful life (RUL) ignore the correlation between physical world data and virtual world data, leading to the low prediction accuracy of RUL and affecting the normal working of rolling element bearing (REB).
Quanbo Lu, Mei Li
doaj   +1 more source

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