A review on vibration-based condition monitoring of rotating machinery
Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal
functioning states are related to specific patterns that can be extracted from vibration signals …
functioning states are related to specific patterns that can be extracted from vibration signals …
A systematic review of deep transfer learning for machinery fault diagnosis
With the popularization of the intelligent manufacturing, much attention has been paid in
such intelligent computing methods as deep learning ones for machinery fault diagnosis …
such intelligent computing methods as deep learning ones for machinery fault diagnosis …
Review of tool condition monitoring in machining and opportunities for deep learning
Tool condition monitoring and machine tool diagnostics are performed using advanced
sensors and computational intelligence to predict and avoid adverse conditions for cutting …
sensors and computational intelligence to predict and avoid adverse conditions for cutting …
Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0
The so-called “smartization” of manufacturing industries has been conceived as the fourth
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …
A survey on deep learning based bearing fault diagnosis
DT Hoang, HJ Kang - Neurocomputing, 2019 - Elsevier
Abstract Nowadays, Deep Learning is the most attractive research trend in the area of
Machine Learning. With the ability of learning features from raw data by deep architectures …
Machine Learning. With the ability of learning features from raw data by deep architectures …
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 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 …
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 convolutional neural network based feature learning and fault diagnosis method for the condition monitoring of gearbox
Feature extraction plays a vital role in intelligent fault diagnosis of mechanical system.
Nevertheless, traditional feature extraction methods suffer from three problems, which are …
Nevertheless, traditional feature extraction methods suffer from three problems, which are …
A review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor
The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …