一种使用高效振动能量采集器的无线电机状态精确分析系统

T. Shimanouchi, O. Toyoda, F. Nakazawa
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引用次数: 4

摘要

本文介绍了一种采用高效能量采集器的无线电机状态精确分析系统。电动机的状态分析需要连续的数据采样。我们开发了一种技术,使振动能量采集器高效,降低了整个系统的能耗。发明了一种无电池无线分析系统,使电机的运行和寿命预测成为可能。高效能量采集器的原始结构是采用磁应变材料棒开发的。当棒被外部振动弯曲时,利用棒周围的线圈产生电力。因此,通过优化使用缓冲板的杆的内应力,提高了能量采集器的效率。能量采集器的谐振频率为90hz,最大电动势为2.7 V,最大功率为28mw,加速度为0.5 g。所述无线电机状态监测系统包括能量采集器、终端设备、协调器和用于数据处理的PC。用于监测和数据传输的终端装置仅使用来自能量采集器的电力进行操作。温度、湿度、供电电压、通信质量每隔3秒监测一次,振动波形每隔5秒监测一次,由终端设备传送给协调器,由PC机处理。这使得电机的状态监测和故障预测成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A wireless motor-condition, precise analysis system using a highly efficient vibration-energy harvester
A wireless motor condition precise analysis system that uses a highly efficient energy harvester is described in this paper. A continuation data sampling is required for the condition analysis of a motor. We developed the technology that makes a vibration energy harvester highly efficient and reduces the energy consumption of the whole system. A battery-less wireless analysis system was created in which the operation and life prediction of a motor was made possible. The original structure of the highly efficient energy harvester was developed using magnetic strain material rods. Electric power is generated using the coils around the rods when the rods are bent by external vibration. Therefore, the efficiency of the energy harvester is raised by optimizing the internal stress of the rods using buffer plates. The energy harvester has a resonant frequency of 90 Hz, a maximum electromotive force of 2.7 V, and a maximum power of 28 mW using 0.5-G acceleration. The wireless motor condition monitoring system includes the energy harvester, an end device, a coordinator, and a PC for data processing. The end device for the monitoring and data transfer is operated using only the electric power from the energy harvester. The monitoring information on the temperature, humidity, supplied voltage, and communication quality every three seconds and for the vibration waveform every five seconds is transmitted to the coordinators by the end device and handled by the PC. This enables for the condition monitoring and fault prediction of the motor.
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