A review on fault detection and diagnosis techniques: basics and beyond
Safety and reliability are absolutely important for modern sophisticated systems and
technologies. Therefore, malfunction monitoring capabilities are instilled in the system for …
technologies. Therefore, malfunction monitoring capabilities are instilled in the system for …
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) …
Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review
A smart factory is a highly digitized and connected production facility that relies on smart
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
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 …
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 …
Machine health monitoring using local feature-based gated recurrent unit networks
In modern industries, machine health monitoring systems (MHMS) have been applied wildly
with the goal of realizing predictive maintenance including failures tracking, downtime …
with the goal of realizing predictive maintenance including failures tracking, downtime …
Infrared thermography-based fault diagnosis of induction motor bearings using machine learning
A Choudhary, D Goyal, SS Letha - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Bearing is one of the most crucial parts in induction motor (IM) as a result there is a constant
call for effective diagnosis of bearing faults for reliable operation. Infrared thermography …
call for effective diagnosis of bearing faults for reliable operation. Infrared thermography …
Rolling element bearing fault diagnosis using convolutional neural network and vibration image
DT Hoang, HJ Kang - Cognitive Systems Research, 2019 - Elsevier
Detecting in prior bearing faults is an essential task of machine health monitoring because
bearings are the vital components of rotary machines. The performance of traditional …
bearings are the vital components of rotary machines. The performance of traditional …
Online fault diagnosis method based on transfer convolutional neural networks
G Xu, M Liu, Z Jiang, W Shen… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Fault detection and diagnosis (FDD) is crucial for stable, reliable, and safe operation of
industrial equipment. In recent years, deep learning models have been widely used in data …
industrial equipment. In recent years, deep learning models have been widely used in data …
Density-based affinity propagation tensor clustering for intelligent fault diagnosis of train bogie bearing
Health monitor of bogie-bearing on the train can ensure constant operation of the rail transit
system. Since the metro or other rail transit have high safety requirements, it is hard to …
system. Since the metro or other rail transit have high safety requirements, it is hard to …