Aircraft engine run-to-failure dataset under real flight conditions for prognostics and diagnostics

M Arias Chao, C Kulkarni, K Goebel, O Fink - Data, 2021 - mdpi.com
A key enabler of intelligent maintenance systems is the ability to predict the remaining useful
lifetime (RUL) of its components, ie, prognostics. The development of data-driven …

Fusing physics-based and deep learning models for prognostics

MA Chao, C Kulkarni, K Goebel, O Fink - Reliability Engineering & System …, 2022 - Elsevier
Physics-based and data-driven models for remaining useful lifetime (RUL) prediction
typically suffer from two major challenges that limit their applicability to complex real-world …

Remaining useful life prediction of aero-engine enabled by fusing knowledge and deep learning models

Y Li, Y Chen, Z Hu, H Zhang - Reliability Engineering & System Safety, 2023 - Elsevier
The remaining useful life (RUL) prediction of a complex engineering system is extremely
significant for ensuring system reliability. The conventional prediction of the RUL based on …

A BiGRU autoencoder remaining useful life prediction scheme with attention mechanism and skip connection

Y Duan, H Li, M He, D Zhao - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Remaining Useful Life (RUL) prediction is one of the most common activities to ensure the
reliability of a degradation system. In previous RUL prediction schemes based on RNN …

Explicit context integrated recurrent neural network for applications in smart environments

RD Baruah, MM Organero - Expert Systems with Applications, 2024 - Elsevier
The development and progress in sensor, communication, and computing technologies
have led to smart environments. In such environments, data can easily be acquired not only …

A two-stage data-driven approach to remaining useful life prediction via long short-term memory networks

H Zhang, X Xi, R Pan - Reliability Engineering & System Safety, 2023 - Elsevier
Accurate remaining useful life (RUL) prediction is of great importance for predictive
maintenance. With the recent advancements in sensor technology and artificial intelligence …

A remaining useful life prognosis of turbofan engine using temporal and spatial feature fusion

C Peng, Y Chen, Q Chen, Z Tang, L Li, W Gui - Sensors, 2021 - mdpi.com
The prognosis of the remaining useful life (RUL) of turbofan engine provides an important
basis for predictive maintenance and remanufacturing, and plays a major role in reducing …

Predictions of component remaining useful lifetime using Bayesian neural network

A Rivas, GK Delipei, J Hou - Progress in Nuclear Energy, 2022 - Elsevier
Abstract The Machine Prognostics and Health Management (PHM) are concerned with the
prediction of the Remaining Useful Lifetime (RUL) of assets. Accurate real-time RUL …

A systematic method of remaining useful life estimation based on physics-informed graph neural networks with multisensor data

Y He, H Su, E Zio, S Peng, L Fan, Z Yang… - Reliability Engineering & …, 2023 - Elsevier
Data-driven models, especially deep learning models, are proposed for remaining useful life
(RUL) estimation with multisensor signals. Various treatments to reduce data sensitivity …

RUL prediction using a fusion of attention-based convolutional variational autoencoder and ensemble learning classifier

I Remadna, LS Terrissa, Z Al Masry… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Predicting the remaining useful life (RUL) is a critical step before the decision-making
process and developing maintenance strategies. As a result, it is frequently impacted by …