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基于摩擦起电效应的贴片式振动可视化(PVV)传感器系统。

Patch-Type Vibration Visualization (PVV) Sensor System Based on Triboelectric Effect.

机构信息

Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, 111 Daedeok-daero 989Beon-gil, Yuseong-gu, Daejeon 34057, Korea.

Center for Nanotechnology and Universities Space Research Association, NASA Ames Research Center, Moffett Field, CA 94035, USA.

出版信息

Sensors (Basel). 2021 Jun 9;21(12):3976. doi: 10.3390/s21123976.

Abstract

Self-powered wireless sensor systems have emerged as an important topic for condition monitoring in nuclear power plants. However, commercial wireless sensor systems still cannot be fully self-sustainable due to the high power consumption caused by excessive signal processing in a mini-electronic computing system. In this sense, it is essential not only to integrate the sensor system with energy-harvesting devices but also to develop simple data processing methods for low power schemes. In this paper, we report a patch-type vibration visualization (PVV) sensor system based on the triboelectric effect and a visualization technique for self-sustainable operation. The PVV sensor system composed of a polyethylene terephthalate (PET)/Al/LCD screen directly converts the triboelectric signal into an informative black pattern on the LCD screen without excessive signal processing, enabling extremely low power operation. In addition, a proposed image processing method reconverts the black patterns to frequency and acceleration values through a remote-control camera. With these simple signal-to-pattern conversion and pattern-to-data reconversion techniques, a vibration visualization sensor network has successfully been demonstrated.

摘要

自供电无线传感器系统已成为核电站状态监测的一个重要课题。然而,由于微型电子计算系统中信号处理过度导致的高功耗,商业无线传感器系统仍然无法完全自给自足。从这个意义上说,不仅要将传感器系统与能量收集装置集成,还必须开发简单的数据处理方法以实现低功耗方案。在本文中,我们报告了一种基于摩擦起电效应的贴片式振动可视化 (PVV) 传感器系统以及一种用于自维持运行的可视化技术。该 PVV 传感器系统由聚对苯二甲酸乙二醇酯 (PET)/Al/LCD 屏幕组成,无需过度信号处理即可直接将摩擦电信号转换为 LCD 屏幕上的信息丰富的黑色图案,从而实现极低的功耗运行。此外,通过远程控制摄像头,提出的图像处理方法可以将黑色图案重新转换为频率和加速度值。通过这些简单的信号到图案的转换和图案到数据的重新转换技术,成功地展示了一个振动可视化传感器网络。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6c4/8227292/fcc13d9ad596/sensors-21-03976-g001.jpg

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