Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
[HTML][HTML] Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods
Abstract Approaches such as Cyber-Physical Systems (CPS), Internet of Things (IoT),
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …
Health status assessment and remaining useful life prediction of aero-engine based on BiGRU and MMoE
Prognostics and health management (PHM) is a critical work to ensure the reliable operation
of industrial equipment, in which health status (HS) assessment and remaining useful life …
of industrial equipment, in which health status (HS) assessment and remaining useful life …
[PDF][PDF] A survey of predictive maintenance: Systems, purposes and approaches
This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …
with emphasis on system architectures, purposes and approaches. In industry, any outages …
A novel deep convolutional neural network-bootstrap integrated method for RUL prediction of rolling bearing
In this study, a novel deep convolutional neural network-bootstrap-based integrated
prognostic approach for the remaining useful life (RUL) prediction of rolling bearing is …
prognostic approach for the remaining useful life (RUL) prediction of rolling bearing is …
Bearing remaining useful life prediction based on regression shapalet and graph neural network
Remaining useful life (RUL) prediction of bearing is essential to guarantee its safe
operation. In recent years, deep learning (DL)-based methods attract a lot of research …
operation. In recent years, deep learning (DL)-based methods attract a lot of research …
A convolutional neural network based degradation indicator construction and health prognosis using bidirectional long short-term memory network for rolling bearings
Health prognosis of rolling bearing is of great significance to improve its safety and
reliability. This paper presents a novel health prognosis method for the rolling bearing based …
reliability. This paper presents a novel health prognosis method for the rolling bearing based …
State of AI-based monitoring in smart manufacturing and introduction to focused section
Over the past few decades, intelligentization, supported by artificial intelligence (AI)
technologies, has become an important trend for industrial manufacturing, accelerating the …
technologies, has become an important trend for industrial manufacturing, accelerating the …
Data-driven capacity estimation for lithium-ion batteries with feature matching based transfer learning method
Accurate capacity estimation is essential in the management of lithium-ion batteries, as it
guarantees the safety and dependability of battery-powered systems. However, direct …
guarantees the safety and dependability of battery-powered systems. However, direct …
Self-attention ConvLSTM and its application in RUL prediction of rolling bearings
Traditional long short-term memory (LSTM) neural networks generally face the challenge of
low training efficiency and poor prediction accuracy for the remaining useful life (RUL) …
low training efficiency and poor prediction accuracy for the remaining useful life (RUL) …