Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Subject Bi-LSTM
Showing results 1 to 2 of 2
| Issue Date | Title | Author(s) |
|---|---|---|
| 2025 | Bearing fault detection using machine learning on vibration and sound signals | Wang, Tianhao |
| 29-Oct-2022 | Frequency Domain Feature Extraction and Long Short-Term Memory for Rolling Bearing Fault Diagnosis | Wang, T; Qin, R; Meng, H; Li, M; Cheng, M; Liu, Y |