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RED: RFID-based Eccentricity Detection for High-speed Rotating Machinery

机译:RED:基于RFID的高速旋转机械偏心检测

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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.
机译:偏心检测是高速旋转机械的关键问题,它关系到机械的稳定性和安全性。工业上用于偏心率检测的常规技术主要基于对某些物理指标的测量,这些指标既昂贵又难以部署。在本文中,我们提出了RED,一种非侵入式,低成本且基于RFID的实时偏心率检测方法。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率检测的有效特征。 RED包括基于马尔可夫链的称为RUM的模型,该模型仅需要从标签中读取一些样本读数即可做出高度准确和精确的判断。我们使用现成的RFID阅读器和标签来实现RED,并在各种情况下评估其性能。总体准确性为93.59%,平均检测延迟为0.68秒。

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