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Multi-objective Optimization of Extreme Learning Machine for Remaining Useful Life Prediction
Given that physics-based models can be difficult to derive, data-driven models have been widely used for remaining useful life (RUL) prediction,...
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Improved similarity based prognostics method for turbine engine degradation with degradation consistency test
Similarity-based prediction methods have gained increasing attention in data-driven remaining useful life (RUL) technologies, mainly because of their...
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Evaluating eXplainable artificial intelligence tools for hard disk drive predictive maintenance
In the last years, one of the main challenges in Industry 4.0 concerns maintenance operations optimization, which has been widely dealt with several...
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Robustness Verification of Deep Neural Networks Using Star-Based Reachability Analysis with Variable-Length Time Series Input
Data-driven, neural network (NN) based anomaly detection and predictive maintenance are emerging as important research areas. NN-based analytics of...
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Forecasting Functional Time Series Using Federated Learning
The need for accurate time series forecasting has questioned the potential of Federated Learning (FL) in solving regression problems with...
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Condition monitoring and life prediction of the turning tool based on extreme learning machine and transfer learning
When the turning tool has worn and failed but the failure is not found, if it continues to be used for processing, it will break, and cause the...
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Remaining useful life predictions for turbofan engine degradation based on concurrent semi-supervised model
As a crucial and expensive component of the aircraft, it is important to effectively predict its remaining useful life (RUL) so as to reduce...
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A data-driven approach based on deep neural networks for lithium-ion battery prognostics
Remaining useful life estimation is gaining attention in many real-world applications to alleviate maintenance expenses and increase system...
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Convolutional neural network based on attention mechanism and Bi-LSTM for bearing remaining life prediction
Good prognostic health management (PHM) plays a crucial role in industrial production and other fields. The accurate prediction of remaining useful...
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Online remaining-useful-life estimation with a Bayesian-updated expectation-conditional-maximization algorithm and a modified Bayesian-model-averaging method
Online remaining-useful-life (RUL) estimation is an effective method with respect to ensuring the safety of complex-huge systems. Generally, current...
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Accelerating Evolutionary Neural Architecture Search for Remaining Useful Life Prediction
Deep neural networks (DNNs) obtained remarkable achievements in remaining useful life (RUL) prediction of industrial components. The architectures of...
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Comparison of Health Indicators Construction for Concrete Structure Using Acoustic Emission Hit and Kullback-Leibler Divergence
This paper investigates the construction of health indicators (HIs) for concrete structures using acoustic emission (AE) hit and Kullback-Leibler...
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A Proposal of Metric for Improving Remaining Useful Life Prediction in Industrial Systems
The deterioration of engineering systems due to wear and working conditions impact directly on their performance, requiring more efficient...
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A New Health Indicator Construction Approach and Its Application in Remaining Useful Life Prediction of Bearings
A good health index (HI) plays an important role in improving the reliability and accuracy of the prediction of remaining useful life (RUL) of...
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Detection and Fault Prediction in Electrolytic Capacitors Using Artificial Neural Networks
Capacitors are electronic components that present a considerable variation in their characteristics during their useful life. After being submitted...
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Research on Machine Learning Method for Equipment Health Management in Industrial Internet of Things
Much industrial equipment integrates multiple types of sensors for data collection and real-time connection with the Industrial Internet of Things...
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AA-LSTM: An Adversarial Autoencoder Joint Model for Prediction of Equipment Remaining Useful Life
Remaining Useful Life (RUL) prediction of equipment can estimate the time when equipment reaches the safe operating limit, which is essential for...
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Performance of Explainable AI Methods in Asset Failure Prediction
Extensive research on machine learning models, which in the majority are black-boxes, created a great need for the development of Explainable...
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Applied Machine Tool Data Condition to Predictive Smart Maintenance by Using Artificial Intelligence
We describe how to integrate data-driven predictive maintenance (PdM) in machine decision-making and data collection and processing. A brief overview...
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Characterization of the State of Health of Electronic Devices for Fostering Safety and Circular Economy
Inspired by the concept of the health of the human body, the state of health (SoH) determination of products has been gaining importance for...