Bearing Fault Diagnosis Using Lightweight and Robust One-Dimensional Convolution Neural Network in the Frequency Domain
Convolution; Convolutional neural networks; Deep learning; Fast Fourier transforms; Fault detection; Frequency domain analysis; Gaussian noise (electronic); Roller bearings; Signal processing; Signal to noise ratio; Time domain analysis; Bearing; Bearing fault diagnosis; Convolution neural network;...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Published: |
MDPI
2023
|
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Convolution; Convolutional neural networks; Deep learning; Fast Fourier transforms; Fault detection; Frequency domain analysis; Gaussian noise (electronic); Roller bearings; Signal processing; Signal to noise ratio; Time domain analysis; Bearing; Bearing fault diagnosis; Convolution neural network; Convolutional neural network; Deep learning; Environmental noise; Faults diagnosis; Frequency domains; One-dimensional; One-dimensional convolutional neural network; Failure analysis; algorithm; Fourier analysis; signal noise ratio; signal processing; Algorithms; Fourier Analysis; Neural Networks, Computer; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio |
|---|