journal article·2025-04Open access

Durable Self‐Powered Wireless IoT Machine Condition Monitoring System Based on an Auto‐Switching Non‐Contact Centrifugal TENG

Idiris Mehamud, Marcus Björling, Pär Marklund, Yijun Shi

Advanced Materials Technologies· Volume 10· Issue 8

Abstract

Abstract The long‐term intelligent machine condition monitoring system is essential in improving maintenance costs and decision‐making. Triboelectric nanogenerator (TENG) has a great advantage in developing self‐powered machine condition monitoring. The main issues preventing TENG for such applications are poor integration to machine components, limited operational range, and weak durability. In this work, durable non‐contact TENG energy harvester adaptive is designed to mechanical shafts for harvesting rotational energy. The harvester is designed to automatically switch to the non‐contact mode by using centrifugal force to avoid manual switching while operating over a wide range of speeds of 0–2000 rpm. The designed TENG generates a high output of up to 25 mW with excellent stability for >20 days of continuous operation and exhibits a high‐power density of 286 W m−3. Moreover, a self‐powered long‐term continuous condition monitoring system is developed from a TENG sensor, energy harvester, and wireless module. The developed system successfully sends possible machine fault frequency every 74 min to the cloud and accessible anywhere. This is the only TENG design reported in the literature that can fully power a Wi‐Fi module to send data. Hence, the result promises the practical application of the system in developing internet of things (IoT) in the Industry.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Sensor Technology and Measurement Systems · Wireless Power Transfer Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Division of Machine Elements Luleå University of Technology Luleå SE‐971 87 Sweden

Funding

Vetenskapsrådet

References (41)

Show source-provided references
1. R.Liu J.Wang in13th Global Congress on Manufacturing and Management (GCMM 2016) 2017 100 02034.
2. C.Yang W.Shen X.Wang 2016 IEEE 20th Int. Conf. on Computer Supported Cooperative Work in Design IEEE Piscataway NJ2016 670.10.1109/CSCWD.2016.7566069 ↗
3. 10.1016/j.eswa.2023.11973810.1016/j.eswa.2023.119738 ↗
4. 10.1007/1-84628-269-1_810.1007/1-84628-269-1_8 ↗
5. 10.1016/j.measurement.2021.10985610.1016/j.measurement.2021.109856 ↗
6. 10.1021/acsnano.0c0980310.1021/acsnano.0c09803 ↗
7. 10.1016/j.ceja.2021.10023710.1016/j.ceja.2021.100237 ↗
8. 10.1002/adsu.20240057510.1002/adsu.202400575 ↗
9. 10.3390/nano1217296010.3390/nano12172960 ↗
10. 10.1016/j.nanoen.2023.10893510.1016/j.nanoen.2023.108935 ↗
11. 10.1016/j.mattod.2020.10.03110.1016/j.mattod.2020.10.031 ↗
12. 10.1007/s00339-018-1942-510.1007/s00339-018-1942-5 ↗
13. 10.1016/j.nanoen.2018.05.04610.1016/j.nanoen.2018.05.046 ↗
14. 10.1016/j.nanoen.2024.10950610.1016/j.nanoen.2024.109506 ↗
15. 10.3390/nano1216279010.3390/nano12162790 ↗
16. 10.3390/jmse1010134810.3390/jmse10101348 ↗
17. 10.1016/j.nanoen.2024.11008410.1016/j.nanoen.2024.110084 ↗
18. 10.1088/1361-665X/ac9e2d10.1088/1361-665X/ac9e2d ↗
19. 10.1016/j.nanoen.2023.10830810.1016/j.nanoen.2023.108308 ↗
20. 10.1002/advs.20220723010.1002/advs.202207230 ↗
21. 10.1007/s40684-023-00569-610.1007/s40684-023-00569-6 ↗
22. 10.1002/adfm.20221340710.1002/adfm.202213407 ↗
23. 10.1016/j.nanoen.2021.10658510.1016/j.nanoen.2021.106585 ↗
24. 10.1016/j.nanoen.2022.10729210.1016/j.nanoen.2022.107292 ↗
25. 10.1002/adfm.20230674910.1002/adfm.202306749 ↗
26. 10.1002/aenm.20200088610.1002/aenm.202000886 ↗
27. 10.1002/aelm.20230011110.1002/aelm.202300111 ↗
28. 10.1016/j.nanoso.2023.10098010.1016/j.nanoso.2023.100980 ↗
29. 10.1002/adma.20231438010.1002/adma.202314380 ↗
30. 10.1021/acsnano.5b0183010.1021/acsnano.5b01830 ↗
31. 10.1038/s41467-021-25047-y10.1038/s41467-021-25047-y ↗
32. 10.3390/nanoenergyadv303001010.3390/nanoenergyadv3030010 ↗
33. 10.1016/j.nanoen.2022.10781610.1016/j.nanoen.2022.107816 ↗
34. 10.1021/nn402491y10.1021/nn402491y ↗
35. 10.1016/j.nanoen.2024.10943910.1016/j.nanoen.2024.109439 ↗
36. 10.1038/ncomms1298510.1038/ncomms12985 ↗
37. M.Salauddin R. M.Toyabur J. Y.Park IEEE Micro Electro Mechanical System IEEE Piscatway NJ2018 233.10.1109/MEMSYS.2018.8346527 ↗
38. 10.1002/aenm.20230005110.1002/aenm.202300051 ↗
39. 10.1016/j.nanoen.2017.02.03610.1016/j.nanoen.2017.02.036 ↗
40. 10.1039/D2EE00900E10.1039/D2EE00900E ↗
41. 10.1016/j.nanoen.2019.05.07310.1016/j.nanoen.2019.05.073 ↗