21 / 2022-02-28 16:06:00
Self-powered Triboelectric Vibration Sensor Network Construction for Overhead Transmission Line Vibration Mapping
transmission lines, aeolian vibration, triboelectric nanogenerator, online monitoring, self-powered sensor network
终稿
Han Wu / State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University
Yicen Liu / Electric Power Research Institute of Sichuan State Grid Company
Wenlong Liao / Electric Power Research Institute of Sichuan State Grid Company
Xinyu Luo / Electric Power Research Institute of Sichuan State Grid Company
Zongxi Zhang / Electric Power Research Institute of Sichuan State Grid Company
Yun Feng / Electric Power Research Institute of Sichuan State Grid Company
The frequent aeolian vibrations on overhead transmission lines potentially endanger the line health, this situation is even worse for the high-voltage long-span lines, which has attracted increased attention focused on the online monitoring of vibrations. However, current vibration monitoring methods have limitations in large-scale distributed measurements for the lack of sustainable power supply of sensors. Herein, a self-powered sensor network for the transmission line aeolian vibration is proposed by utilizing the triboelectric nanogenerator (TENG) as the sensor to acquire vibration signals of transmission lines. As driven by Maxwell’s displacement current, the TENG is able to provide real-time vibration amplitude and frequency signals with high accuracy and sensitivity. Moreover, a group of TENGs was installed on the transmission line to compose the sensor network. Integrated with the developed LabView software, a visual vibration mapping system enabled by the collected multi-point voltage signals has been demonstrated to graph the vibration distribution information of the overall line. This work renders an efficient and intuitive vibration monitoring method for the overhead transmission lines, which is beneficial to the early warning of the line fatigue faults that further ensures the power system stability.

 
重要日期
  • 会议日期

    09月25日

    2022

    09月29日

    2022

  • 08月15日 2022

    提前注册日期

  • 09月10日 2022

    报告提交截止日期

  • 11月10日 2022

    注册截止日期

  • 11月30日 2022

    初稿截稿日期

  • 11月30日 2022

    终稿截稿日期

主办单位
IEEE DEIS
承办单位
Chongqing University
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