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一个基于多源人类运动能量收集的自我感知和自我供电的可穿戴系统

Daning Hao^1,2, Yuchen Gong^2,3, Jiaoyi Wu^2,4

¹School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China.

Small (Weinheim an der Bergstrasse, Germany)

|February 11, 2024

概括

这项研究介绍了一种自动供电的可穿戴系统,它从腰部运动和膝盖运动中收集能量. 该系统能够实现自我传感功能,并使用先进的能量清理技术有效地为可穿戴设备提供动力.

科学领域:

可穿戴技术是可穿戴的技术.
节能采集节能采集节能采集
生物医学工程生物医学工程

背景情况:

可穿戴设备需要持续供电,通常由电池寿命限制.
人体在运动时会产生大量浪费的动能.
现有的可穿戴设备的能量采集方法在效率和整合方面面临挑战.

研究的目的:

开发一种自我感应和自我供电的可穿戴系统 (SS-WS).
为了从腰部运动和膝盖负运动中获取能量,为供电设备.
整合深度学习以使用收获的能量进行运动识别.

主要方法:

使用三度自由度的 triboelectric 纳米发电机 (TDF-TENG) 来收集腰部运动能量.
使用负能量收割器 (NEH) 来回收膝盖负能量.
应用了一种Gate Recurrent Unit深度学习模型来处理动作识别的 triboelectric信号.

主要成果:

结合深度学习的TDF-TENG,准确地识别了人类运动状态.
NEH在8公里/小时时速下实现了27.01mW的输出功率,在3Hz时达到0.3W/kg的功率密度.
证明了可穿戴设备的有效自传感和电源.

结论:

拟议的SS-WS为自动供电的可穿戴系统提供了可行的解决方案.
整合TENGs和NEH可以有效地从人类运动中获取能量.
深度学习增强了可穿戴系统的自我感知能力.

关键词:

能源采集能源采集频率上升转换频率上升转换自动驱动的自动驱动汽车自动感应自动感应.穿戴式设备是一种可穿戴的设备.

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