A Novel Fault Diagnosis Method for Rolling Bearing Based on Improved Sparse Regularization via Convex Optimization
Structural health monitoring and fault state identification of key components, such as rolling bearing, located in the mechanical main drive system, have a vital significance. The acquired fault signal of rolling bearing always presents the obvious nonlinear and nonstationary characteristics. Moreov...
Saved in:
| Main Authors: | Dongjie Zhong, Cancan Yi, Han Xiao, Houzhuang Zhang, Anding Wu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/2169364 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Novel Sparse Enhancement Neural Network for Rolling Bearing Fault Diagnosis
by: Yong Zhang, et al.
Published: (2022-01-01) -
Sparse Regularization With Reverse Sorted Sum of Squares via an Unrolled Difference-of-Convex Approach
by: Takayuki Sasaki, et al.
Published: (2025-01-01) -
ROLLING BEARING FAULT DIAGNOSIS BASED ON ADAPTIVE FEATURE SELECTION <italic>k</italic>-SUB CONVEX HULL
by: HU AiRu, et al.
Published: (2024-04-01) -
Rolling Bearing Fault Diagnosis Based on Recurrence Plot
by: Zheming Chen, et al.
Published: (2024-01-01) -
Rolling Bearing Fault Diagnosis via Temporal-Graph Convolutional Fusion
by: Fan Li, et al.
Published: (2025-06-01)