File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1038/s41467-020-15950-1
- Scopus: eid_2-s2.0-85084452862
- PMID: 32393741
Supplementary
- Citations:
- Appears in Collections:
Article: Randomized resonant metamaterials for single-sensor identification of elastic vibrations
| Title | Randomized resonant metamaterials for single-sensor identification of elastic vibrations |
|---|---|
| Authors | |
| Issue Date | 2020 |
| Citation | Nature Communications, 2020, v. 11, n. 1, article no. 2353 How to Cite? |
| Abstract | Vibrations carry a wealth of useful physical information in various fields. Identifying the multi-source vibration information generally requires a large number of sensors and complex hardware. Compressive sensing has been shown to be able to bypass the traditional sensing requirements by encoding spatial physical fields, but how to encode vibration information remains unexplored. Here we propose a randomized resonant metamaterial with randomly coupled local resonators for single-sensor compressed identification of elastic vibrations. The disordered effective masses of local resonators lead to highly uncorrelated vibration transmissions, and the spatial vibration information can thus be physically encoded. We demonstrate that the spatial vibration information can be reconstructed via a compressive sensing framework, and this metamaterial can be reconfigured while maintaining desirable performance. This randomized resonant metamaterial presents a new perspective for single-sensor vibration sensing via vibration transmission encoding, and potentially offers an approach to simpler sensing devices for many other physical information. |
| Persistent Identifier | http://hdl.handle.net/10722/369001 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jiang, Tianxi | - |
| dc.contributor.author | Li, Chong | - |
| dc.contributor.author | He, Qingbo | - |
| dc.contributor.author | Peng, Zhi Ke | - |
| dc.date.accessioned | 2026-01-16T02:40:13Z | - |
| dc.date.available | 2026-01-16T02:40:13Z | - |
| dc.date.issued | 2020 | - |
| dc.identifier.citation | Nature Communications, 2020, v. 11, n. 1, article no. 2353 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/369001 | - |
| dc.description.abstract | Vibrations carry a wealth of useful physical information in various fields. Identifying the multi-source vibration information generally requires a large number of sensors and complex hardware. Compressive sensing has been shown to be able to bypass the traditional sensing requirements by encoding spatial physical fields, but how to encode vibration information remains unexplored. Here we propose a randomized resonant metamaterial with randomly coupled local resonators for single-sensor compressed identification of elastic vibrations. The disordered effective masses of local resonators lead to highly uncorrelated vibration transmissions, and the spatial vibration information can thus be physically encoded. We demonstrate that the spatial vibration information can be reconstructed via a compressive sensing framework, and this metamaterial can be reconfigured while maintaining desirable performance. This randomized resonant metamaterial presents a new perspective for single-sensor vibration sensing via vibration transmission encoding, and potentially offers an approach to simpler sensing devices for many other physical information. | - |
| dc.language | eng | - |
| dc.relation.ispartof | Nature Communications | - |
| dc.title | Randomized resonant metamaterials for single-sensor identification of elastic vibrations | - |
| dc.type | Article | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1038/s41467-020-15950-1 | - |
| dc.identifier.pmid | 32393741 | - |
| dc.identifier.scopus | eid_2-s2.0-85084452862 | - |
| dc.identifier.volume | 11 | - |
| dc.identifier.issue | 1 | - |
| dc.identifier.spage | article no. 2353 | - |
| dc.identifier.epage | article no. 2353 | - |
| dc.identifier.eissn | 2041-1723 | - |
