电容感应
水下
信号(编程语言)
灵活性(工程)
计算机科学
材料科学
声学
数学
统计
海洋学
操作系统
物理
地质学
程序设计语言
作者
Yang Deng,Wei Zhai,Chongyang Fu,Qizheng Li,Yanqiang Li,Huaisong Zhao,Xiao-Xiong Wang
出处
期刊:Nanotechnology
[IOP Publishing]
日期:2025-06-19
卷期号:36 (30): 305501-305501
标识
DOI:10.1088/1361-6528/ade5fb
摘要
With the increasing importance of low-frequency signals in underwater monitoring, earthquake early warning, environmental noise analysis, and biomedical imaging, traditional sensor technologies face challenges such as limited flexibility, slow response time, and poor adaptability. Although existing sensors, such as electromagnetic, piezoelectric, and capacitive sensors, have made progress in certain areas, their applications are often restricted by complex environments. This paper innovatively proposes anin-situvibration monitoring method, designing a low-frequencyin-situdetection system based on triboelectric nanogenerator technology. The system not only enables efficient low-frequency signal detection in complex underwater environments but also, by incorporating machine learning algorithms, identifies different signal sources, achieving accurate distinction of intrinsic signals. The application of this technology realizes the concept ofin-situdetection, breaking through the limitations of traditional sensor systems and providing a new solution for real-time monitoring of low-frequency signals.
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