Research on Industrial Process Fault Diagnosis Method Based on DMCA-BiGRUN
With the rising automation and complexity level of industrial systems, the efficiency and accuracy of fault diagnosis have become a critical challenge. The convolutional neural network (CNN) has shown some success in the fault diagnosis field. However, typical convolutional kernels are commonly fixe...
Saved in:
| Main Authors: | Feng Yu, Changzhou Zhang, Jihan Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/15/2331 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep Learning Method for Bearing Fault Diagnosis
by: LIU Xiu, et al.
Published: (2022-08-01) -
Hierarchical Convolution-Transformer Framework for Gear Fault Diagnosis Under Severe Noise
by: Qiushi He, et al.
Published: (2025-01-01) -
Rolling Bearing Fault Diagnosis Based on Recurrence Plot
by: Zheming Chen, et al.
Published: (2024-01-01) -
A Dual-Attentive Multimodal Fusion Method for Fault Diagnosis Under Varying Working Conditions
by: Yan Chu, et al.
Published: (2025-06-01) -
Enhanced analog circuit fault diagnosis via continuous wavelet transform and dual-stream convolutional fusion
by: Zhiwen Hou, et al.
Published: (2025-06-01)