- A Bearing Fault Diagnosis Method Based on a Residual Network ...🔍
- A bearing fault diagnosis method based on adaptive residual ...🔍
- A Bearing Fault Diagnosis Method Based on an Improved Depth ...🔍
- Bearing Fault Diagnosis Using Residual Network and Attention ...🔍
- Rolling bearing fault diagnosis method based on improved residual ...🔍
- Bearing fault diagnosis method based on improved deep residual ...🔍
- A fault diagnosis method of rolling bearing based on improved deep ...🔍
- Bearing fault diagnosis method based on improved deep residual Si...🔍
A Bearing Fault Diagnosis Method Based on a Residual Network ...
A Bearing Fault Diagnosis Method Based on a Residual Network ...
This article proposes a model for fault diagnosis under time-varying operating conditions that combines a residual network model (ResNet) and a gate recurrent ...
A Bearing Fault Diagnosis Method Based on a Residual Network ...
The diagnosis of bearing faults is an important guarantee for the healthy operation of mechanical equipment. Due to the time-varying working ...
A bearing fault diagnosis method based on adaptive residual ...
Convolutional neural networks have been widely applied in the fault diagnosis domain of rolling bearings. However, as the number of network ...
A Bearing Fault Diagnosis Method Based on an Improved Depth ...
To solve the problem that it is difficult to accurately identify bearing damage degree under strong noise, an Improved Deep Residual Network based on ...
Bearing Fault Diagnosis Using Residual Network and Attention ...
Therefore, this paper proposes a fault diagnosis method based on attention mechanism and residual neural network (FaultCNN). Firstly, a residual attention ...
Rolling bearing fault diagnosis method based on improved residual ...
A fault diagnosis method for improved residual shrinkage network of rolling bearings is proposed in this paper.
Bearing fault diagnosis method based on improved deep residual ...
Firstly, the Siamese neural network is applied to extract features with shared weights to achieve an expansion in the number of fault samples.
A fault diagnosis method of rolling bearing based on improved deep ...
Improved deep residual shrinkage network (IDRSN) are proposed and applied to rolling bearing fault diagnosis under noise backgrounds.
Bearing fault diagnosis method based on improved deep residual Si...
Firstly, the Siamese neural network is applied to extract features with shared weights to achieve an expansion in the number of fault samples.
Bearing Fault Reconstruction Diagnosis Method Based on ResNet ...
The axle box in the bogie system of subway trains is a key component connecting primary damper and the axle. In order to extract deep features and ...
Rolling Bearing Fault Diagnosis based on Residual Neural Network
PDF | div class="Section0"> Because rolling bearings have been working in an environment with complex and variable working conditions and large noise.
A novel bearing fault diagnosis method using deep residual learning ...
Knowledge-based methods are capable of providing promising solution to bearing diagnosis problem with high accuracy performance thanks to effectively processing ...
Bearing Fault Reconstruction Diagnosis Method Based on ResNet ...
Firstly, multi-layer stacked convolutional kernels and methods to insert them into ultra-deep residual networks are developed. Then, the ...
A Bearing Fault Diagnosis Method Based on a Residual Network ...
The diagnosis of bearing faults is an important guarantee for the healthy operation of mechanical equipment. Due to the time-varying working conditions of ...
Lightweight Bearing Fault Diagnosis Method Based on Improved ...
A lightweight bearing fault detection approach based on an improved residual network is presented to solve the shortcomings of previous ...
A rolling bearing fault diagnosis method based on Markov transition ...
A rolling bearing fault diagnosis method based on Markov transition field and multi-scale Runge-Kutta residual network, Simin Ding, ...
A multibranch residual network for fault-diagnosis of bearings
Time-frequency domain analysis methods are used to diagnose faults in bearings by extracting the features of fault signals. Given that a fault signal is ...
A bearing fault diagnosis method based on adaptive residual ... - OUCI
List of references · Yan · Wang, Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical fault diagnosis of bearings, ...
A graph neural network-based bearing fault detection method - Nature
proposed a data enhancement technique, using deep convolutional neural network with residual learning algorithm as the main structure to obtain ...
Bearing Fault Diagnosis Method Based on Convolutional Neural ...
The + in the figure is the summation of corresponding elements of the feature graph. The residual neural network is passed to the previous layer ...