首页|A self-powered triboelectric nanosensor based on track vibration energy harvesting for smart railway

A self-powered triboelectric nanosensor based on track vibration energy harvesting for smart railway

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  • NETL
  • NSTL
  • Elsevier
Rail transport plays a major role in the development of a nation’s economy. Due to the high maintenance requirementsof train tracks, traditional monitoring sensors need to be connected to the power grid. The rail surfaceenvironment is complex, and there is a lack of power supply equipment. Therefore, a track vibration energyharvester-based self-powered triboelectric nanosensor (TVH-TENS) is designed in this paper. The TVH-TENSsystem has five modules: motion transformation, rectification correction, dual channel power generation, energystorage and deep learning. The motion transformation module uses a bevel gear set with one-way bearingsto transform the track’s two-way linear vibration into one-way rotational motion, addressing both circuitrectification and motion transformation issues simultaneously. The voltage signal output of the triboelectricgenerator is used for deep learning to classify variables and live monitoring. Experimental results reveal that theTVH-TENS system achieves a mean power output of 6.69 W with sinusoidal input of 6 mm amplitude, 6 Hzfrequency and 3 Ω external load in MTS bench experiments. The deep learning accuracy of each variable exceeds98.3 %. The high-performance TVH-TENS can power wireless sensor networks by harvesting vibration energywhile also acting as a monitoring sensor. This system provides a reference method framework for intelligenttrack.

Energy harvestingTriboelectric nano sensorSmart RailwayTVHDeep learning

Yifan Chen、Hongjie Tang、Daning Hao、Tingsheng Zhang、Xiaofeng Xia、Mingyu Wang、Zutao Zhang、Peigang Li

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School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, PR China

School of Information Science & Technology, Southwest Jiaotong University, Chengdu 611756, PR China

School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, PR China||Yibin Research Institute, Southwest Jiaotong University, Yibin 64000, PR China

School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, PR China

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2025

10.1016/j.seta.2025.104203

Sustainable Energy Technologies and Assessments

Sustainable Energy Technologies and Assessments

SCI
ISSN：2213-1388
年,卷(期)：2025.75(Mar.)
  • 43