A comprehensive review on convolutional neural network in machine fault diagnosis
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …
increasingly significant to ensure safe equipment operation and production. Consequently …
Challenges and opportunities of AI-enabled monitoring, diagnosis & prognosis: A review
Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …
prognosis, and health management, occupies an increasingly important position in reducing …
Fault diagnosis of electric impact drills using thermal imaging
A Glowacz - Measurement, 2021 - Elsevier
Fault diagnosis enables to make savings related to maintenance. The presented work
describes fault diagnosis method based on analysis of thermal images. An original method …
describes fault diagnosis method based on analysis of thermal images. An original method …
Intelligent fault diagnosis of rolling bearings under imbalanced data conditions using attention-based deep learning method
J Li, Y Liu, Q Li - Measurement, 2022 - Elsevier
Data-driven intelligent method has been widely used in fault diagnostics. However, it is
observed that previous research studies focusing on imbalanced datasets for fault diagnosis …
observed that previous research studies focusing on imbalanced datasets for fault diagnosis …
A hybrid deep-learning model for fault diagnosis of rolling bearings
Detection accuracy of bearing faults is crucial in saving economic loss for industrial
applications. Deep learning is capable of producing high accuracy for bearing fault …
applications. Deep learning is capable of producing high accuracy for bearing fault …
Convolutional neural network fault classification based on time-series analysis for benchmark wind turbine machine
Fault detection and classification are considered as one of the most mandatory techniques
in nowadays industrial monitoring. The necessity of fault monitoring is due to the fact that …
in nowadays industrial monitoring. The necessity of fault monitoring is due to the fact that …
Challenges and opportunities of deep learning models for machinery fault detection and diagnosis: A review
In the age of industry 4.0, deep learning has attracted increasing interest for various
research applications. In recent years, deep learning models have been extensively …
research applications. In recent years, deep learning models have been extensively …
A brief review of acoustic and vibration signal-based fault detection for belt conveyor idlers using machine learning models
Due to increasing demands for ensuring the safety and reliability of a system, fault detection
(FD) has received considerable attention in modern industries to monitor their machines …
(FD) has received considerable attention in modern industries to monitor their machines …
A deep multi-signal fusion adversarial model based transfer learning and residual network for axial piston pump fault diagnosis
Y He, H Tang, Y Ren, A Kumar - Measurement, 2022 - Elsevier
Deep learning has made remarkable achievements in fault diagnosis. However, the working
conditions of the axial piston pump are diverse, and the distribution of the data is not the …
conditions of the axial piston pump are diverse, and the distribution of the data is not the …
Cbgru: A detection method of smart contract vulnerability based on a hybrid model
In the context of the rapid development of blockchain technology, smart contracts have also
been widely used in the Internet of Things, finance, healthcare, and other fields. There has …
been widely used in the Internet of Things, finance, healthcare, and other fields. There has …