Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective
In the Engineering discipline, prognostics play an essential role in improving system safety,
reliability and enabling predictive maintenance decision-making. Due to the adoption of …
reliability and enabling predictive maintenance decision-making. Due to the adoption of …
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects
O Serradilla, E Zugasti, J Rodriguez, U Zurutuza - Applied Intelligence, 2022 - Springer
Given the growing amount of industrial data in the 4th industrial revolution, deep learning
solutions have become popular for predictive maintenance (PdM) tasks, which involve …
solutions have become popular for predictive maintenance (PdM) tasks, which involve …
A hybrid predictive maintenance approach for CNC machine tool driven by Digital Twin
As a typical manufacturing equipment, CNC machine tool (CNCMT) is the mother machine
of industry. Fault of CNCMT might cause the loss of precision and affect the production if …
of industry. Fault of CNCMT might cause the loss of precision and affect the production if …
Data-driven remaining useful life prediction via multiple sensor signals and deep long short-term memory neural network
Remaining useful life (RUL) prediction is very important for improving the availability of a
system and reducing its life cycle cost. This paper proposes a deep long short-term memory …
system and reducing its life cycle cost. This paper proposes a deep long short-term memory …
Feature extraction for data-driven remaining useful life prediction of rolling bearings
H Zhao, H Liu, Y Jin, X Dang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A variety of data-driven methods have been proposed to predict remaining useful life (RUL)
of key component for rolling bearings. The accuracy of data-driven RUL prediction model …
of key component for rolling bearings. The accuracy of data-driven RUL prediction model …
Deep learning approach towards accurate state of charge estimation for lithium-ion batteries using self-supervised transformer model
Accurate state of charge (SOC) estimation of lithium-ion (Li-ion) batteries is crucial in
prolonging cell lifespan and ensuring its safe operation for electric vehicle applications. In …
prolonging cell lifespan and ensuring its safe operation for electric vehicle applications. In …
Failure prognosis and applications—A survey of recent literature
Fault diagnosis and prognosis are some of the most crucial functionalities in complex and
safety-critical engineering systems, and particularly fault diagnosis, has been a subject of …
safety-critical engineering systems, and particularly fault diagnosis, has been a subject of …
Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis
Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs). The
ability to model and forecast remaining useful life of these batteries enables UAV reliability …
ability to model and forecast remaining useful life of these batteries enables UAV reliability …
Recent advances in prognostics and health management for advanced manufacturing paradigms
Manufacturing paradigms have played their important roles in modern industry. In recent 20
years, production systems of advanced manufacturing paradigms (eg mass customization …
years, production systems of advanced manufacturing paradigms (eg mass customization …
Prognostics and remaining useful life prediction of machinery: advances, opportunities and challenges
As the fundamental and key technique to ensure the safe and reliable operation of vital
systems, prognostics with an emphasis on the remaining useful life (RUL) prediction has …
systems, prognostics with an emphasis on the remaining useful life (RUL) prediction has …