RED: RFID-based Eccentricity Detection for High-speed Rotating Machinery
RED: RFID-based Eccentricity Detection for High-speed Rotating Machinery
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DOI：
10.1109/infocom.2018.8485873
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发表时间：
2018-04
期刊：
影响因子：
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通讯作者：
Yilun Zheng;Yuan He;Meng Jin;Xiaolong Zheng;Yunhao Liu
中科院分区：
文献类型：
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作者：
Yilun Zheng;Yuan He;Meng Jin;Xiaolong Zheng;Yunhao Liu
偏心检测是高速旋转机械的关键问题，关系到机械的稳定性和安全性。工业上传统的偏心检测技术主要是基于对某些物理指标的测量，成本高，部署困难。在本文中，我们提出了RED，一种非侵入式，低成本，实时的基于rfid的偏心检测方法。与现有的基于rfid的传感方法不同，RED利用标签读数的时间和相位分布作为偏心检测的有效特征。RED包括一个基于马尔可夫链的RUM模型，它只需要从标签上读取几个样本就可以做出高度准确的判断。我们使用商用RFID阅读器和标签实现RED，并评估其在各种场景下的性能。总体准确率为93.59%，平均检测延迟为0.68秒。
Eccentricity detection is a crucial issue for highspeed rotating machinery, which concerns the stability and safety of the machinery. Conventional techniques in industry for eccentricity detection are mainly based on measuring certain physical indicators, which are costly and hard to deploy. In this paper, we propose RED, a non-intrusive, low-cost, and realtime RFID-based eccentricity detection approach. Differing from the existing RFID-based sensing approaches, RED utilizes the temporal and phase distributions of tag readings as effective features for eccentricity detection. RED includes a Markov chain based model called RUM, which only needs a few sample readings from the tag to make a highly accurate and precise judgement. We implement RED with commercial-of-the-shelf RFID reader and tags, and evaluate its performance across various scenarios. The overall accuracy is 93.59% and the detection latency is 0.68 seconds in average.