Research on Signal Denoising of Pumped-Storage Units Based on Parameter-Adaptive VMD and Wavelet Thresholding
Tianmin Li, Yuechao Wu, Fengque Pei · 2026
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Description
Tianmin Li, Yuechao Wu, and Fengque Pei present a 2026 study on cleaning vibration signals from pumped-storage power units, the reversible turbines that balance the grid. Their signals twist and jump, and strong background noise buries the fault clues. The team's method pairs adaptive signal splitting, tuned by an improved swarm search, with wavelet threshold cleaning in two passes, screening split parts by how alike they look before the second pass.
Tests on simulated shaft signals and on real station data beat rival methods, lifting the signal-to-noise ratio and cutting error clearly. Cleaner signals give later fault analysis firmer ground. The authors frame the method as practical groundwork for watching the health of these large machines.
Catalog record
| CREATOR | Tianmin Li, Yuechao Wu, Fengque Pei |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 44067 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |