Lu Yingli, Liu Changxin, Wang Yi, Hao Zhijie, Chen Chutian, Dong Bo, Zhou Xun
Marine Engineering College, Dalian Maritime University, Dalian 116000, PR China.
Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, School of Energy and Power Engineering, Dalian University of Technology, Dalian, 116024, PR China.
Nanoscale. 2025 May 9;17(18):11547-11563. doi: 10.1039/d5nr00647c.
Transmission line icing is a major natural hazard affecting overhead power lines, especially under specific meteorological conditions such as low temperatures, high humidity, and strong winds. Ice overload may cause line faults, structural damage, and even collapse of poles and towers. Traditional ice monitoring approaches have restrictions, such as discontinuous measurement and the inability to support the self-powered operation of the monitoring system. A self-powered monitoring method that utilizes a triboelectric nanogenerator (TENG) and a micro thermoelectric generator (MTEG) to assess the thickness and growth dynamics of ice on transmission lines is presented. A TENG-based ice thickness sensing model (HP-TENG) employing a PR/PDMS composite friction layer fabricated an AAO template method is established, integrated with bismuth telluride-based MTEG modules for enhanced energy harvesting and sensing capabilities. A prototype for monitoring the growth state of ice on transmission lines based on a TENG-MTEG is developed. An experiment system that integrates HP-TENGs, MTEGs, a signal processing unit, and a signal transmission unit is constructed. The system incorporates a multi-directional ice-cover growth signal processing unit, which can concurrently collect and process signals from six HP-TENG channels. The experimental results indicate that the HP-TENGs can accurately sense the ice thickness in the range of 10 mm-20 mm, achieving a maximum error of only 2.14%. It effectively monitors ice growth rates between 0.02 mm s and 1 mm s, with a maximum error of 3.65%. The MTEG unit demonstrates a maximum output voltage of 1.15 V and a maximum current of 180 mA. Furthermore, the multi-directional ice-cover growth signal processing unit processes the output signals from the HP-TENG and wirelessly transmits them to the microcontroller (MCU).
输电线路覆冰是影响架空输电线路的主要自然灾害，尤其是在低温、高湿度和强风等特定气象条件下。冰荷载可能导致线路故障、结构损坏，甚至杆塔倒塌。传统的覆冰监测方法存在局限性，如测量不连续，且无法支持监测系统的自供电运行。本文提出了一种利用摩擦纳米发电机（TENG）和微型热电发电机（MTEG）来评估输电线路覆冰厚度和生长动态的自供电监测方法。建立了一种基于TENG的冰厚度传感模型（HP-TENG），该模型采用AAO模板法制备的PR/PDMS复合摩擦层，并与基于碲化铋的MTEG模块集成，以增强能量收集和传感能力。开发了一种基于TENG-MTEG的输电线路覆冰生长状态监测原型。构建了一个集成HP-TENG、MTEG、信号处理单元和信号传输单元的实验系统。该系统包含一个多方向覆冰生长信号处理单元，可同时收集和处理来自六个HP-TENG通道的信号。实验结果表明，HP-TENG能够在10毫米至20毫米的范围内准确感测冰厚度，最大误差仅为2.14%。它能有效监测0.02毫米/秒至1毫米/秒之间的冰生长速率，最大误差为3.65%。MTEG单元的最大输出电压为1.15伏，最大电流为180毫安。此外，多方向覆冰生长信号处理单元处理来自HP-TENG的输出信号，并将其无线传输到微控制器（MCU）。
