Patch-Type Vibration Visualization (PVV) Sensor System Based on Triboelectric Effect
Autor: | Byun-Young Chung, Myeong-Lok Seol, Young-Chul Choi, Dae-Sic Jang, Sun Jin Kim, Jong-Hwan Kim |
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Rok vydání: | 2021 |
Předmět: |
Computer science
condition monitoring Image processing TP1-1185 02 engineering and technology 010402 general chemistry 01 natural sciences Biochemistry Signal Vibration Analytical Chemistry Electric Power Supplies Electronic engineering Nanotechnology triboelectric effect Electrical and Electronic Engineering pattern-to-data decoding Instrumentation Triboelectric effect Data processing Signal processing Chemical technology Communication Condition monitoring Signal Processing Computer-Assisted 021001 nanoscience & nanotechnology Atomic and Molecular Physics and Optics signal-to-pattern encoding 0104 chemical sciences Visualization self-sustainable vibration visualization sensor system Electronics 0210 nano-technology Wireless sensor network |
Zdroj: | Sensors (Basel, Switzerland) Sensors, Vol 21, Iss 3976, p 3976 (2021) |
ISSN: | 1424-8220 |
Popis: | 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. |
Databáze: | OpenAIRE |
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