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 fault diagnosis
Showing results 1 to 5 of 5
| Issue Date | Title | Author(s) |
|---|---|---|
| 11-May-2021 | Bearing Fault Diagnosis Based on Optimized Variational Mode Decomposition and 1-D Convolutional Neural Networks | Wang, Q; Yang, C; Wan, H; Deng, D; Nandi, AK |
| 13-Feb-2023 | Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016 | Chen, X; Yang, R; Xue, Y; Huang, M; Ferrero, R; Wang, Z |
| 23-Jun-2021 | Fault Diagnosis Approach of Main Drive Chain in Wind Turbine Based on Data Fusion | Xu, Z; Yang, P; Zhao, Z; Lai, CS; Lai, LL; Wang, X |
| 4-Sep-2023 | A Novel Ensemble-Learning-Based Convolution Neural Network for Handling Imbalanced Data | Wu, X; Wen, C; Wang, Z; Liu, W; Yang, J |
| 23-Nov-2022 | Vibration Image Representations for Fault Diagnosis of Rotating Machines: A Review | Ahmed, HOA; Nandi, AK |