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Wireless Rail Fastener Looseness Detection Based on MEMS Accelerometer and Vibration Entropy

机译:基于MEMS加速度计和振动熵的无线轨道紧固件松动检测

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摘要

In this paper, we present an automatic inspection system based on micro motion sensors for detecting the "looseness" of rail fasteners. The system is composed of a low-power MEMS accelerometer and a Global System for Mobile Communications (GSM) unit, and can detect loose fasteners and upload the results to a cloud server in real-time. Finite Element Method (FEM) is used to analyze rail vibration characteristics in the vertical direction as the rail is excited by mechanical pulse inputs. On this basis, the Chao-Shen Entropy theory was applied to identify fastener looseness reliably. In addition, field experiments were also conducted on Datong-Qinhuangdao Railway, the longest coal-transport railway in the world. The experimental results show that fastener looseness can slow down the attenuation of rail vibration in the time domain and produce a large entropy value. Using the method of amplitude entropy, loose fasteners can be identified reliably for looseness factor >60%. The proposed system has been experimental validated to enable real-time detection of railway fastener looseness and could potentially bring significant benefits for the day-to-day maintenance of railways.
机译:在本文中,我们介绍了一种基于微观运动传感器的自动检查系统,用于检测轨道紧固件的“松动”。该系统由低功耗MEMS加速度计和移动通信(GSM)单元的全球系统组成,并且可以实时检测松动的紧固件并将结果上传到云服务器。有限元方法(FEM)用于分析垂直方向上的轨道振动特性,因为通过机械脉冲输入激发轨道。在此基础上,应用了潮神熵理论以可靠地识别紧固件松动。此外,还在大同 - 秦皇岛铁路上进行了现场实验,是世界上最长的煤炭运输铁路。实验结果表明,紧固件松动可以减缓时域内轨道振动的衰减并产生大的熵值。使用幅度熵的方法,可以可靠地识别松动的紧固件,以便松散为60%。该拟议的系统已经进行了实验验证,以便能够实时检测铁路紧固件松动,并且可能为铁路的日常维护带来显着的益处。

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