A Hybrid Deep Learning Framework for Multi-Sensor PMSM Fault Diagnosis Based on SVMD Denoising and Spatiotemporal Feature Fusion.
- DOI
- 10.3390/s26175537
- Published
- 2026 Aug 31
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s26175537,
title = {A Hybrid Deep Learning Framework for Multi-Sensor PMSM Fault Diagnosis Based on SVMD Denoising and Spatiotemporal Feature Fusion.},
author = {Guan M and Peng Y and Xie Y},
year = {2026},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s26175537},
url = {https://doi.org/10.3390/s26175537}
}RIS
TY - JOUR TI - A Hybrid Deep Learning Framework for Multi-Sensor PMSM Fault Diagnosis Based on SVMD Denoising and Spatiotemporal Feature Fusion. AU - Guan M AU - Peng Y AU - Xie Y PY - 2026 JO - Sensors (Basel, Switzerland) DO - 10.3390/s26175537 UR - https://doi.org/10.3390/s26175537 ER -
APA
M, G., Y, P., & Y, X. (2026). A Hybrid Deep Learning Framework for Multi-Sensor PMSM Fault Diagnosis Based on SVMD Denoising and Spatiotemporal Feature Fusion.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26175537
Source records
- pubmed · retrieved 2026-11-10T08:34:42.452Z