Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
Deep learning and its applications to machine health monitoring
Abstract Since 2006, deep learning (DL) has become a rapidly growing research direction,
redefining state-of-the-art performances in a wide range of areas such as object recognition …
redefining state-of-the-art performances in a wide range of areas such as object recognition …
A new convolutional neural network-based data-driven fault diagnosis method
Fault diagnosis is vital in manufacturing system, since early detections on the emerging
problem can save invaluable time and cost. With the development of smart manufacturing …
problem can save invaluable time and cost. With the development of smart manufacturing …
Deep learning for smart manufacturing: Methods and applications
Smart manufacturing refers to using advanced data analytics to complement physical
science for improving system performance and decision making. With the widespread …
science for improving system performance and decision making. With the widespread …
A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
In recent years, intelligent fault diagnosis algorithms using machine learning technique have
achieved much success. However, due to the fact that in real world industrial applications …
achieved much success. However, due to the fact that in real world industrial applications …
A review on the application of deep learning in system health management
Given the advancements in modern technological capabilities, having an integrated health
management and diagnostic strategy becomes an important part of a system's operational …
management and diagnostic strategy becomes an important part of a system's operational …
A new deep transfer learning based on sparse auto-encoder for fault diagnosis
Fault diagnosis plays an important role in modern industry. With the development of smart
manufacturing, the data-driven fault diagnosis becomes hot. However, traditional methods …
manufacturing, the data-driven fault diagnosis becomes hot. However, traditional methods …
[HTML][HTML] Machine learning methods for wind turbine condition monitoring: A review
This paper reviews the recent literature on machine learning (ML) models that have been
used for condition monitoring in wind turbines (eg blade fault detection or generator …
used for condition monitoring in wind turbines (eg blade fault detection or generator …
Deep learning algorithms for bearing fault diagnostics—A comprehensive review
In this survey paper, we systematically summarize existing literature on bearing fault
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …
Multiscale convolutional neural networks for fault diagnosis of wind turbine gearbox
This paper proposes a novel intelligent fault diagnosis method to automatically identify
different health conditions of wind turbine (WT) gearbox. Unlike traditional approaches …
different health conditions of wind turbine (WT) gearbox. Unlike traditional approaches …