ECNN: A Low-complex, Adjustable CNN for Industrial Pump Monitoring Using Vibration Data
| Author: | Jonas Ney, Norbert Wehn |
|---|---|
| URL: | https://ieeexplore.ieee.org/document/11010817 |
| DOI: | https://doi.org/10.1109/CIESCompanion65073.2025.11010817 |
| ISBN: | 979-8-3315-0849-4 |
| ISBN: | 979-8-3315-0850-0 |
| Parent Title (English): | 2025 IEEE Symposium on Computational Intelligence on Engineering/Cyber Physical Systems Companion (CIES Companion) |
| Secondary publication (full text): | https://doi.org/10.48550/arXiv.2503.07401 |
| Publisher: | IEEE |
| Place of publication: | Piscataway, NJ |
| Document Type: | Conference Proceeding |
| Language: | English |
| Publication year: | 2025 |
| Year of first Publication: | 2025 |
| Release Date: | 2026/01/15 |
| Page Number: | 5 |
| First Page: | 1 |
| Last Page: | 5 |
| Faculties / Organisational entities: | RPTU in Kaiserslautern / Fachbereich Elektrotechnik und Informationstechnik / Entwurf Mikroelektronischer Systeme |
| Open access state: | Grün Open-Access |
| RPTU: | Kaiserslautern |
| Research funding: | BMBF |
| Sonstige | |
| Created at the RPTU: | Yes |