摩擦电效应
纳米发生器
定子
方位(导航)
材料科学
转子(电动)
电压
断层(地质)
汽车工程
电容器
振动
信号(编程语言)
工程类
电气工程
声学
计算机科学
复合材料
物理
人工智能
地震学
地质学
程序设计语言
作者
Qinkai Han,Ziyuan Jiang,Yun Kong,Fulei Chu
出处
期刊:IEEE-ASME Transactions on Mechatronics
[Institute of Electrical and Electronics Engineers]
日期:2022-12-01
卷期号:27 (6): 4686-4696
被引量:6
标识
DOI:10.1109/tmech.2022.3164022
摘要
A prebent membrane-based triboelectric nanogenerator (PM-TENG) was proposed to harvest rotational energy; its application in diagnosing faults in rotating machinery was then explored. A PM array was realized by pressing two sides of each arch membrane into the radial grooves of a rotor disk, and a PM-TENG was formed together with a stator disk with interdigital electrodes pasted on the surface. Variations in output voltage and current with load resistance were tested, and the effects of design parameters on the output characteristics were discussed. It is demonstrated that the proposed PM-TENG has self-powered characteristics by charging the load capacitor and effectively driving micropowered electronic devices. Two test rigs were constructed for fault diagnosis tests in the rotating machinery. Fault characteristic frequencies were identified using the output current model of the PM-TENG. Fast Fourier transform and deep learning models were used to classify only bearing and gear-bearing hybrid faults, respectively. The results showed that the PM-TENG output current can be used to diagnose typical faults in rotating machinery; the classification accuracy exceeded 92%, which is only slightly lower than that based on the vibration signal. The proposed PM-TENG has application potential for rotating machinery fault diagnosis.
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