High output triboelectric nanogenerator based on PTFE and cotton for energy harvester and human motion sensor

Recently, a novel mechanical energy harvesting method named triboelectric nanogenerator (TENG) is reported, and it has aroused great repercussions in the academic fields. But, the complex preparation process still limits its wide application. In this paper, the cotton film was used as the triboelectric material to fabricate a novel wearable TENG (W-TENG). The polytetrafluoroethylene (PTFE) film and cotton film play the role of triboelectric pair. The W-TENG can be used to harvest low-frequency mechanical energy in our environment, especially for human body mechanical energy, and then convert them to electrical energy. In addition, the cotton coated with conductive ink plays the role of conductive material for TENG. The V_oc and I_sc of W-TENG can reach 556 V and 26 μA, respectively. As for the maximum power density of W-TENG, it can arrive at 0.66 mW/cm². Also, a combined W-TENG was proposed to improve the electrical output. Moreover, the W-TENG can play the role of human motion sensor for human walking posture monitoring. This will open up a new path for the preparation of high output TENG at low cost, and promote the TENG devices in the field of sports monitoring.     

基于遗传小波神经网络的机器人腕力传感器动态建模研究

提出一种基于改进遗传算法进化小波神经网络用于机器人腕力传感器动态建模的新方法,介绍了该算法原理.该方法利用腕力传感器的动态标定数据,用改进的遗传算法来优化小波神经网络结构和参数,建立腕力传感器的动态模型.结果表明,采用遗传小波神经网络进行腕力传感器动态建模,能克服误差反向传播算法存在易陷入局部极小点的缺点,网络的复杂度、收敛性和泛化能力得到了好的综合,建模的速度和精度得到提高. 关键词： 腕力传感器 动态建模 小波神经网络 遗传算法