A Self-Powered and Highly Accurate Vibration Sensor Based on Bouncing-Ball Triboelectric Nanogenerator for Intelligent Ship Machinery Monitoring

被引：66

作者：

Du, Taili ^{[1
,2
]}

Zuo, Xusheng ^{[1
]}

Dong, Fangyang ^{[1
]}

Li, Shunqi ^{[1
]}

Mtui, Anaeli Elibariki ^{[1
]}

Zou, Yongjiu ^{[1
,2
]}

Zhang, Peng ^{[1
,2
]}

Zhao, Junhao ^{[1
]}

Zhang, Yuewen ^{[1
,2
]}

Sun, Peiting ^{[1
]}

Xu, Minyi ^{[1
]}

机构：

[1] Dalian Maritime Univ, Marine Engn Coll, Dalian 116026, Peoples R China

[2] Dalian Maritime Univ, Collaborat Innovat Res Inst Autonomous Ship, Dalian 116026, Peoples R China

来源：

MICROMACHINES | 2021年 / 12卷 / 02期

基金：

中国国家自然科学基金;

关键词：

self-powered; vibration sensor; triboelectric nanogenerator; machinery monitoring; intelligent ship; FEATURE-EXTRACTION; ENERGY; PISTON; SPEED;

D O I：

10.3390/mi12020218

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

With the development of intelligent ship, types of advanced sensors are in great demand for monitoring the work conditions of ship machinery. In the present work, a self-powered and highly accurate vibration sensor based on bouncing-ball triboelectric nanogenerator (BB-TENG) is proposed and investigated. The BB-TENG sensor consists of two copper electrode layers and one 3D-printed frame filled with polytetrafluoroethylene (PTFE) balls. When the sensor is installed on a vibration exciter, the PTFE balls will continuously bounce between the two electrodes, generating a periodically fluctuating electrical signals whose frequency can be easily measured through fast Fourier transform. Experiments have demonstrated that the BB-TENG sensor has a high signal-to-noise ratio of 34.5 dB with mean error less than 0.05% at the vibration frequency of 10 Hz to 50 Hz which covers the most vibration range of the machinery on ship. In addition, the BB-TENG can power 30 LEDs and a temperature sensor by converting vibration energy into electricity. Therefore, the BB-TENG sensor can be utilized as a self-powered and highly accurate vibration sensor for condition monitoring of intelligent ship machinery.

引用

页数：14

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