Deep Clustering Bearing Fault Diagnosis Method Based on Local ...

An unsupervised bearing fault diagnosis method based on deep clustering is proposed. In this method, an autoencoder is initially applied to the signal spectrum.

[PDF] Deep Clustering Bearing Fault Diagnosis Method Based on ...

Experiments conducted on the Case Western Reserve University bearing datasets show that the proposed unsupervised bearing fault diagnosis method can find ...

(PDF) Deep Clustering Bearing Fault Diagnosis Method Based on ...

To address this, an unsupervised bearing fault diagnosis method based on deep clustering is proposed. In this method, an autoencoder is ...

Deep Clustering Bearing Fault Diagnosis Method Based on Local ...

To address this, an unsupervised bearing fault diagnosis method based on deep clustering is proposed. In this method, an autoencoder is ...

Deep Clustering Bearing Fault Diagnosis Method Based on Local ...

To address this, an unsupervised bearing fault diagnosis method based on deep clustering is proposed. In this method, an autoencoder is initially applied to ...

Deep Clustering Bearing Fault Diagnosis Method Based on Local ...

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Em · Comments.

Bearing Fault Diagnosis Method Based on Deep Convolutional ...

[9] used the empirical mode decomposition (EMD) method to extract features from the bearing vibration signals and presented a kurtosis-based method to select ...

A Regularized Deep Clustering Method for Fault Trend Analysis

(2018) proposed local feature-based gated recurrent unit networks. (LFGRU) ... multiscale ica method for slewing bearing fault detection and diagnosis ...

A Bearing Fault Diagnosis Method Based on a Residual Network ...

Therefore, the detection of bearing faults is often carried out under time-varying operating conditions. A general intelligent fault diagnosis ...

A systematic review of rolling bearing fault diagnoses based on ...

This paper aims to give a comprehensive overview of Deep Learning (DL) based on bearing fault diagnosis.

An Intelligent Multi-Local Model Bearing Fault Diagnosis Method ...

In summary, data-driven methods are more suitable than the traditional spectrum analysis methods based on vibration signals considering the requirements of ...

Deep learning fault diagnosis method based on global optimization ...

Xia et al. used SDAE-based deep neural network (DNN) to learn more representative features and improved the accuracy of bearing fault diagnosis [13]. Jia et al ...

A graph neural network-based bearing fault detection method - Nature

To address this problem, we propose a graph neural network-based bearing fault detection (GNNBFD) method. The method first constructs a graph ...

A new bearing fault diagnosis method based on multi-scale CNN ...

Fault diagnosis is mainly completed by analyzing the signal data that reflects the intrinsic characteristics such as vibration signals [2], ...

Bearing fault detection by using graph autoencoder and ensemble ...

proposed a method for diagnosing bearing faults based on deep convolutional neural networks (DCNN), which can achieve more accurate fault ...

A multi-stage semi-supervised improved deep embedded clustering ...

[33] proposed a bearing fault diagnosis method that included two data augmentation methods (sample-based method and data-based method) and five ...

A bearing fault diagnosis method based on a convolutional spiking ...

Combined with the spiking convolutional layers, the network fully extracts the spatial-temporal features from the bearing vibration signals.

Bearing Fault Diagnosis Method Based on Deep Convolutional ...

In particular, low-level features containing local characteristics and accurate details in the hidden layers are combined to improve the diagnostic performance.

Research on High-Speed Train Bearing Fault Diagnosis Method ...

Traditional bearing fault diagnosis methods struggle to effectively extract distinctive, domain-invariable characterizations from one-dimensional vibration ...

A multi-stage semi-supervised improved deep embedded clustering ...

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding · Engineering, Computer Science. IEEE Access · 2021.