基于自供电状态监测的地铁列车宽带振动能量采集

Hailing Fu, Wenzhe Song, Yong Qin, E. Yeatman
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引用次数: 8

摘要

利用机械非线性和综合多模态振动,提出并研制了一种适合地铁列车自供电状态监测的宽带振动能量采集器。采用数据驱动的方法,利用列车转向架运行振动数据进行收割机设计。收割机的设计是不引人注目的,同时在宽带宽上表现出良好的能量收集性能。在这项工作中,首先对现场振动数据进行分析,确定设计目标。然后,提出了一种宽带收割机,并进行了实现和评估。收割机由一个预拉伸的承载梁和一组在其自由端具有排斥磁力的微梁组成。在这种设计下,得到了具有非线性动力学特性的多振型收割机。该收割机在频扫和伪随机测试中表现出良好的宽带宽性能,说明其在自供电状态监测应用中的能力。
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Broadband Vibration Energy Harvesting from Underground Trains for Self-Powered Condition Monitoring
A broadband vibration energy harvester tailored for self-powered condition monitoring of underground trains is proposed and developed using mechanical non-linearity and integrated multi-mode vibration. A data-driven approach is adopted for harvester design using operational vibration data on a train bogie. The harvester is designed to be unobtrusive while exhibiting good performance in harvesting energy over a wide bandwidth. In this work, the on-site vibration data are first analysed with the design goals identified. Then, a broadband harvester is proposed, implemented and evaluated. The harvester consists of a pre-stretched hosting beam and a group of micro-beams with repulsive magnetic forces on their free ends. A multiple vibration-mode harvester with non-linear dynamics is obtained in such a design. This harvester exhibits good performance over a broad bandwidth in frequency sweep and pseudo-random tests, illustrating its capability in self-powered condition monitoring applications.
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