Advanced bearing fault detection at varying rotational speeds using PSO-optimized SVM and CDET feature selection
Abstract In this exploration, we introduce a novel intelligent hybrid methodology for multiclass bearing fault detection under varying rotational speeds. Unlike previous studies, our approach combines empirical mode decomposition (EMD), wavelet packet decomposition (WPD), and a comprehensive attribu...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-07-01
|
| Series: | Journal of Engineering and Applied Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44147-025-00683-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Be the first to leave a comment!