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| 1 | A real-time sensing system based on triboelectric nanogenerator for dynamic response of bridges显示文摘The strain of bridges under traffic loads is time-varying and of small amplitude(~10^(-6)),which is a type of cumulative response and needs long-term continuous monitoring.To precisely capture the time-varying responses,a dynamic strain triboelectric nanogenerator(TENG)sensor with superior response capability,sensitivity,self-powered,and long-term stability is proposed in this paper.An analytical correlation between the structural strain response signal and the detected electrical signal is established for long-term continuous quantitative strain measurements based on the principles of contact electrification and electrostatic induction.A series of experiments are conducted to investigate the output performance of the proposed lateral-sliding mode TENG sensors.The results reveal that,with the loading condition with frequencies lower than 10 Hz,the time-varying strain responses of the steel bridge within the range of 3 to 150 microstrains can also be detected with high precision of 0.1 microstrains.And it achieves long-term stability after 10000 loading cycles compared with commercial sensors.The proposed novel sensing theory and method based on TENG technology can be applied as a new alternative approach for monitoring realtime structural strain information quantitatively with general applicability and feasibility for bridges. | ZHANG He HUANG KangXu ZHOU YuHui SUN LiangFeng ZHANG ZhiCheng LUO JiKui | 2022 | Science China(Technological Sciences)2022，65，11： | 1 |
| 2 | Segment differential aggregation representation and supervised compensation learning of ConvNets for human action recognition显示文摘With more multi-modal data available for visual classification tasks,human action recognition has become an increasingly attractive topic.However,one of the main challenges is to effectively extract complementary features from different modalities for action recognition.In this work,a novel multimodal supervised learning framework based on convolution neural networks(Conv Nets)is proposed to facilitate extracting the compensation features from different modalities for human action recognition.Built on information aggregation mechanism and deep Conv Nets,our recognition framework represents spatial-temporal information from the base modalities by a designed frame difference aggregation spatial-temporal module(FDA-STM),that the networks bridges information from skeleton data through a multimodal supervised compensation block(SCB)to supervise the extraction of compensation features.We evaluate the proposed recognition framework on three human action datasets,including NTU RGB+D 60,NTU RGB+D 120,and PKU-MMD.The results demonstrate that our model with FDA-STM and SCB achieves the state-of-the-art recognition performance on three benchmark datasets. | REN ZiLiang ZHANG QieShi CHENG Qin XU ZhenYu YUAN Shuai LUO DeLin | 2024 | Science China(Technological Sciences)2024，67，1： | 0 |
| 3 | 用于井下振动测量的自发电振动传感器的研制显示文摘井下钻具的共振可能会损坏钻具甚至造成井下事故,对井下振动进行实时测量非常有必要。然而目前常规传感器的井下电池和电缆的供电方式会降低钻探效率,因此具有井下发电功能的传感器将更加适宜实际工况。针对此情况,研制了一种具有自发电功能的振动传感器,其利用振动工况诱导传感器内部纳米材料相互摩擦进行发电,同时利用摩擦电信号与振动信号的对应关系实现对振动的测量。室内试验结果表明,传感器的输出信号幅值可达7.3 V,最大发电功率约0.84μW,振动测量范围为0~13 Hz,振动测量误差小于5%,可在小于250℃的温度范围内正常工作。研究成果可为井下发电及井下超高温传感器技术的研究提供一定的借鉴。 | 冯彦军 吴川 杨朔 | 2023 | 矿业安全与环保2023，50，4： | 0 |
| 4 | 基于惯性传感的越野滑雪技术动作识别显示文摘越野滑雪技术动作识别能够有效帮助运动员优化滑行策略和改进技术动作。传统方法存在空间受限、变更装备及传感器数目较多的问题,因此,提出了一种基于惯性传感的越野滑雪动作识别方法。对惯性数据进行低通滤波的预处理,实现越野滑雪子技术动作区间划分。生成时域频域特征并对其特征值进行归一化和主成分分析(PCA)。设计了支持向量机(SVM)分类器,实现对越野滑雪技术动作的识别。实验结果表明:该方法对3种越野滑雪子动作双杖推撑(DP)滑行,对角跨步(DS),踢腿双杖推撑(KDP)的识别率高达95.4%,证明了所提方法为越野滑雪动作识别提供了一种新颖高效的解决方案。 | 张振鹏 杨云 陈亮 何剑 | 2022 | 传感器与微系统2022，41，12： | 0 |
| 5 | Self-powered forest ambient monitoring microsystem based on wind energy hybrid nanogenerators显示文摘In response to the call for zero-carbon energy supply for Internet of Things(IoTs)applications and to get rid of the dependence of traditional distributed IoTs devices on batteries,the invention of nanogenerators that can convert wind energy in the surrounding environment into electrical energy have received widespread attention.Herein,a wind energy hybrid harvester(WH-EH)combining a soft-friction and positive-directional triboelectric nanogenerator(SP-TENG)and a hierarchical rotating electromagnetic nanogenerator(HR-EMG)is reported to construct a self-powered forest environment monitoring microsystem.With the design of thin inner wall beams and comb-shaped electrodes,the SP-TENG is able to change the output into positivedirectional,which can be stored directly in the energy storage device,breaking the limitation of the alternating positive and negative output of conventional TENGs.In addition,the HR-EMG embeds coils in the cup lid to make the most of the available space in the external package.In the WH-EH,a layered structure,including the HR-EMG and SP-TENG is adopted to jointly utilize wind energy for both higher output and higher utilization.In order to effectively implement wireless monitoring of the forest environment,the WH-EH is further utilized to develop a self-powered forest environment monitoring microsystem by powering the IoTs sensor nodes,realizing ambient temperature and humidity sampling and wireless transmission,so as to achieve the purpose of preventing forest fires.It is believed that the development of the WH-EH and the self-powered forest environment monitoring microsystem provides diverse options for the practicalization of self-powered IoTs systems and the energy supply problem of IoTs sensor networks. | LI BoYuan QIU Yu HUANG Peng TANG WenJie ZHANG XiaoSheng | 2022 | Science China(Technological Sciences)2022，65，10： | 0 |
| 6 | 用于人体运动与语音识别的柔性可拉伸摩擦电传感器显示文摘为提高可穿戴摩擦电传感器电极的柔性与可拉伸性,设计了一种基于商用水性高分子导电凝胶电极的摩擦电传感器,且在电极一侧表面加工得到微观结构。测试结果表明该传感器具有约100%的伸长率与优异的耐卷曲扭折性。该传感器的电压与电流信号对外界压力具有良好的线性响应,且对传感器的拉伸状态不敏感。当施加外力为50 N时(频率1 Hz),输出峰值电压为109 V,峰值电流为1.3μA;当频率从1.0 Hz变化到3.0 Hz时,峰值电压几乎无变化,峰值电流从0.65μA变化到2.1μA。将该传感器应用于人体运动与语音识别时,电压信号可以对每种动作表现出特异的波形信号,实现了4种动作以及6种礼貌用语的检测与识别,表明其在人体运动与生物特征识别用可穿戴传感器领域具有良好的应用价值。 | 蔡婷婷 尹振华 马鸣宇 贾磊 王子恒 杨云 | 2024 | 微纳电子技术2024，61，1： | 0 |
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