风力发电
环境科学
能量收集
计算机科学
能量(信号处理)
工程类
电气工程
物理
量子力学
作者
Heng Tang,Wandi Chen,Zhigang Peng,Yu Zhang,Xiongtu Zhou,Chaoxing Wu,Yongai Zhang
标识
DOI:10.1021/acsaelm.4c02159
摘要
Wind conditions are crucial in agricultural production, and wind vectors play a significant role in agricultural planting plans. However, traditional anemometers rely on external power sources such as lithium batteries, while wind energy in farmlands is usually neglected. This paper proposes an intelligent wind vector monitoring system based on a dual-module triboelectric nanogenerator (DM-TENG), which consists of a fan-blade type soft-contact triboelectric nanogenerator (FBTSC-TENG) and a disc-shaped triboelectric nanogenerator (DS-TENG). FBTSC-TENG collects wind energy in the environment to power the temperature and humidity sensors, while determining wind speed through the frequency of voltage pulses. DS-TENG can monitor wind direction, identifying 8 wind directions through output pulse signals and deep learning algorithms. Therefore, the DM-TENG proposed in this study is expected to play a significant role in the field of smart agriculture in the future.
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