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  5. Hybrid Triboelectric‐Electromagnetic Magnetic Energy Harvester‐Based Sensing for Wireless Monitoring of Transmission Lines

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Article
en
2022

Hybrid Triboelectric‐Electromagnetic Magnetic Energy Harvester‐Based Sensing for Wireless Monitoring of Transmission Lines

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0 Files

en
2022
Vol 18 (27)
Vol. 18
DOI: 10.1002/smll.202107221

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Zhihao Yuan
Jin Xu
Ruonan Li
+5 more

Abstract

Abstract Magnetic energy is an abundant and persistent form of energy radiating from various sources. Here, a hybrid triboelectric‐electromagnetic magnetic energy harvester (HMEH) system consisting of a modified pendulum unit is proposed, interacting mechanically with two multilayered TENGs and remotely with Cu coils. Systematic studies are conducted on magneto‐mechano‐energy conversion from power transmission lines. The pendulum is made out of a thin PET plate, with two permanent magnets stuck at each side of the free end of the PET plate. Two multilayered TENGs (each of which has one layer fixed at the same angle while other layers are set free) are located at both sides of the pendulum unit. The coils and the magnets make up the electromagnetic generator (EMG). Multilayered TENGs are connected in parallel with the EMG (each unit is connected to an independent rectifying bridge), and it is possible to charge a 100 µF capacitor to 4.78 V within 55 s. The HMEH system is used to power up a thermometer continuously via a 47 µF capacitor. Furthermore, a design for a wireless early warning system for potential fire hazards due to overheating is realized, revealing potential applications for self‐powered wireless monitoring of transmission lines.

How to cite this publication

Zhihao Yuan, Jin Xu, Ruonan Li, Baocheng Wang, Chengcheng Han, Yapeng Shi, Zhiyi Wu, Zhong Lin Wang (2022). Hybrid Triboelectric‐Electromagnetic Magnetic Energy Harvester‐Based Sensing for Wireless Monitoring of Transmission Lines. , 18(27), DOI: https://doi.org/10.1002/smll.202107221.

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Publication Details

Type

Article

Year

2022

Authors

8

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/smll.202107221

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