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首页> 外文期刊>IEEJ Transactions on Electrical and Electronic Engineering >Design and Data Processing of Galloping Online Monitoring System for Positive Feeder of High-Speed Railway Catenary in Gale Area
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Design and Data Processing of Galloping Online Monitoring System for Positive Feeder of High-Speed Railway Catenary in Gale Area

机译:大风区域高速铁路链纳里阳性馈线的疾驰在线监控系统的设计和数据处理

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摘要

To monitor the galloping state of the catenary positive feeder of the Lanzhou-Urumqi high-speed railway in the gale area, on the basis of previous research results, an online multi-point distributed galloping monitoring system based on wireless sensor network (WSN) was designed, and the author improves the design of each part of the catenary positive feeder galloping monitoring system to enhance its availability and reliability. By the system to collect accelerations of each galloping monitoring point, and the displacement is obtained by integrating the acceleration twice, but the integration result was seriously distorted because of the trends. A localization algorithm is proposed to correct the galloping signal waveform. Firstly, in accordance with a detailed analysis of ensemble empirical mode decomposition (EEMD) anti-modal aliasing principle and the steps of the waveform correction method, the original signal was decomposed to obtain ten intrinsic modal functions (IMFs). Secondly, with the IMFs' characteristics as basis, a new method of trend extraction was introduced to extract and eliminate the trends in the original signal. Finally, through the analysis of the measured signal of wire galloping, the feasibility and effectiveness of the proposed method were verified by comparing its results with those of the moving average method, and the galloping trajectory of the wire is obtained by curve fitting. (c) 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
机译:为了监测大风地区兰州 - 乌鲁姆奇高速铁路的链苯式阳性喂食器的疾驰状态,根据先前的研究结果,基于无线传感器网络(WSN)的在线多点分布式疾驰监测系统是设计,作者改进了链纳式馈线捕捞监测系统的每个部分的设计,以增强其可用性和可靠性。通过系统收集每个疾驰监测点的加速度,并通过将加速度集成两次获得位移,但是由于趋势的趋势,整合结果严重扭曲了。提出了定位算法来纠正疾驰的信号波形。首先,根据集合经验模式分解(EEMD)反模式混溶原理的详细分析和波形校正方法的步骤,将原始信号分解以获得十个固有的模态函数(IMFS)。其次,以IMF的特征为基础,引入了一种新的趋势提取方法,以提取和消除原始信号中的趋势。最后,通过分析测量的电线疾驰信号,通过将其结果与移动平均方法的结果进行比较,并通过曲线拟合获得了导线的疾驰轨迹,从而验证了所提出方法的可行性和有效性。 (c)2021日本电气工程师研究所。由Wiley Wendericals LLC出版。

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