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Self-charging power module for multidirectional ultra-low frequency mechanical vibration monitoring and energy harvesting

Author

Listed:
  • Huang, Mingkun
  • Long, Kaixiang
  • Luo, Yuecong
  • Li, Jingxing
  • Su, Cuicui
  • Gao, Xiangming
  • Guo, Shishang

Abstract

Timely monitoring of abnormal vibration of machinery in highly harsh environments is essential to ensure the safe operation of mechanical systems. This paper uses a self-charging power module to harvest energy to provide sustainable power for monitoring multidirectional ultra-low frequency mechanical vibrations. The power generation unit consists mainly of a spherical electromagnetic triboelectric hybrid nanogenerator (SETE-HNG). It is equipped with advanced sensing functions to support deep learning to identify signals with different directions of vibration, different frequencies, and different amplitudes of vibration, thereby enhancing the high-precision perception function. The accuracy of the prediction results is as high as 98.6622%, 100%, and 99.3333%, respectively. A Power Management Circuitry (PMC) has been meticulously crafted to maximize the utilization of vibrational energy. It efficiently charges a 40 mAh lithium polymer battery to 3.3 V in just 26 min, all without the requirement of an external power source. This advancement facilitates self-powered Global Positioning System (GPS) tracking of vibrational signals. Moreover, the stored energy is harnessed to energize a microcontroller and a low-power Bluetooth module. This enables real-time monitoring of mechanical vibrations via a mobile phone. The design presented in this paper is a testament to the potential of self-powered multidirectional mechanical vibration monitoring, contributing significantly to the safety and efficiency of mechanical systems.

Suggested Citation

  • Huang, Mingkun & Long, Kaixiang & Luo, Yuecong & Li, Jingxing & Su, Cuicui & Gao, Xiangming & Guo, Shishang, 2024. "Self-charging power module for multidirectional ultra-low frequency mechanical vibration monitoring and energy harvesting," Applied Energy, Elsevier, vol. 361(C).
    • Handle: RePEc:eee:appene:v:361:y:2024:i:c:s0306261924002381
    DOI: 10.1016/j.apenergy.2024.122855
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    References listed on IDEAS

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    2. Yan Zhang & Yafei Wang & Ying Guan & Yongjun Zhang, 2022. "Peptide-enhanced tough, resilient and adhesive eutectogels for highly reliable strain/pressure sensing under extreme conditions," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Wang, Lu & Fei, Zhenxuan & Duan, Congsheng & Han, Xiangguang & Li, Min & Gao, Wendi & Xia, Yong & Jia, Chen & Lin, Qijing & Zhao, Yihe & Li, Zhikang & Zhao, Libo & Jiang, Zhuangde & Maeda, Ryutaro, 2024. "Self-sustained and self-wakeup wireless vibration sensors by electromagnetic-piezoelectric-triboelectric hybrid energy harvesting," Applied Energy, Elsevier, vol. 355(C).
    4. Hao Wu & Steven Wang & Zuankai Wang & Yunlong Zi, 2021. "Achieving ultrahigh instantaneous power density of 10 MW/m2 by leveraging the opposite-charge-enhanced transistor-like triboelectric nanogenerator (OCT-TENG)," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
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