Multi-Parameter Optimized Triboelectric Nanogenerator Based Self-Powered Sensor Network for Broadband Aeolian Vibration Online-Monitoring of Transmission Lines

Overhead transmission lines are vulnerable to aeolian vibrations that threaten the operation of the power grid. A triboelectric nanogenerator (TENG) based self-powered system offers a desirable way for vibration online-monitoring with potential for large-scale deployment. In this work, a self-powered sensor network constructed by active vibration sensor (AVS) units with a spring-mass based TENG (S-TENG) is reported for effective energy harvesting and broadband vibration sensing. The basic TENG with structural parameters is first discussed from the aspects of efficiency and response characteristics, then the spring constant and mass weight are also adjusted for S-TENGs with different optimal operation regions, thus the overall vibration amplitude and frequency response are further enhanced by the mutual compensation of S-TENGs with a weight allocation strategy. Furthermore, the S-TENGs are combined with external circuits to compose the AVS units, which are deployed in a distributed manner on a simulated transmission line to demonstrate a self-powered wireless warning system and an aeolian vibration mapping system, enabling abnormal vibration warnings and vibration distribution monitoring over the whole line. This work represents a novel strategy for utilizing TENG technology for transmission line aeolian vibration monitoring and provides valuable guidance for further sensor network construction and power grid visualization.

Automated summary

This work presents a self-powered sensor network based on TENG technology for aeolian vibration monitoring in overhead transmission lines. The study enhances the vibration sensing capability by adjusting structural parameters and weight, and successfully applies it to practical warning systems and vibration distribution monitoring systems.