Search
Search Results
-
Predictive maintenance applied to mission critical supercomputing environments: remaining useful life estimation of a hydraulic cooling system using deep learning
Given the growth and availability of computing power, artificial intelligence techniques have been applied to industrial equipment and computing...
-
VisPro: a prognostic SqueezeNet and non-stationary Gaussian process approach for remaining useful life prediction with uncertainty quantification
Rotating machinery is essential to modern life, from power generation to transportation and a host of other industrial applications. Since such...
-
Estimation of Remaining Useful Life for Turbofan Engine Based on Deep Learning Networks
Having accurate prediction on the health of machines in manufacturing can lead to a profitable organization if the operations and maintenance...
-
Capsule Network Based on Double-layer Attention Mechanism and Multi-scale Feature Extraction for Remaining Life Prediction
The era of big data provides a platform for high-precision RUL prediction, but the existing RUL prediction methods, which effectively extract key...
-
Wasserstein distance based multi-scale adversarial domain adaptation method for remaining useful life prediction
Accurate remaining useful life (RUL) prediction can formulate timely maintenance strategies for mechanical equipment and reduce the costs of...
-
A novel spatio-temporal hybrid neural network for remaining useful life prediction
Remaining useful life (RUL) prediction is a crucial mission for the prognostic and health management (PHM) of machinery equipment in modern industry....
-
Predictive Maintenance Optimization Under Stochastic Production in Complex Systems
This paper focuses on predictive maintenance optimization under stochastic production in complex systems using prognostic Remaining Useful Life (RUL)...
-
A transformer with layer-cross decoding for remaining useful life prediction
Remaining useful life (RUL) prediction is critical for industrial equipment status detection, and the accurate prediction results provide...
-
AutoML for Predictive Maintenance: One Tool to RUL Them All
Automated machine learning (AutoML) deals with the automatic composition and configuration of machine learning pipelines, including the selection and...
-
Multi-scale memory-enhanced method for predicting the remaining useful life of aircraft engines
To guarantee the safe operation of machinery and reduce its maintenance costs, estimating its remaining useful life (RUL) is a crucial task. Hence,...
-
Coins in the library: the creation of a digital collection of Roman Republican coins
In 2001, Rutgers University Libraries (RUL) accepted a substantial donation of Roman Republican coins. The work to catalog, house, digitize,...
-
Machine Learning Based Remaining Useful Life Estimation—Concept and Case Study
With advancements in technology and machinery, human dependencies on them are increasing. This increased reliance makes maintenance in industrial...
-
A MDA-LSTM network for remaining useful life estimation of lithium batteries
Remaining useful life (RUL) of energy storage batteries estimation is of great significance to battery failure warning and battery safety. Previous...
-
Remaining Useful Life Estimation for Railway Gearbox Bearings Using Machine Learning
Gearbox bearing maintenance is one of the major overhaul cost items for railway electric propulsion systems. They are continuously exposed to...
-
Enhancing EV lithium-ion battery management: automated machine learning for early remaining useful life prediction with innovative multi-health indicators
Addressing the need for multiple health indicators is critical to improving prediction accuracy and reducing the limitation of reliance on a single...
-
Benchmark: Remaining Useful Life Predictor for Aircraft Equipment
We propose a predictive maintenance application as a benchmark problem for verification of neural networks (VNN). It is a deep learning based...
-
Prognostics based on the generalized diffusion process with parameters updated by a sequential Bayesian method
The realistic degradation process for the engineering equipment is generally stochastic and complicated owing to the uncertain operational condition...
-
Predictive Maintenance Under Absence of Sensor Data
In industrial settings, component breakdowns can cause production delays, until repaired or replaced, and incur high costs. To address this issue,...
-
A deep learning-based two-stage prognostic approach for remaining useful life of rolling bearing
Remaining useful life (RUL) prediction is of great importance to improve the reliability and availability of machinery. Traditional rolling bearing...
-
LIME: Long-Term Forecasting Model for Desalination Membrane Fouling to Estimate the Remaining Useful Life of Membrane
Membrane fouling is one of the major problems in desalination processes as it can cause a severe drop in the quality and quantity of the permeate...