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Visual analytics towards axle health of high-speed train based on large-scale scatter image

机译：基于大规模分散图像的高速列车轴健康的视觉分析

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摘要

Axle is an important part of high-speed train. The axle is the key component connecting the train wheelset, which has a great impact on the train safety. The health monitoring of axles is very important for the safe and smooth operation of trains. The axle health detection is a complex process of multi-factor coupling, which faces the problems of health model construction. From the perspective of big data visual analysis, this paper helps people find the information behind the big data of high-speed railway axle monitoring, and makes a prediction and analysis of the health status of high-speed railway axle operation. Starting from the present situation of scatter plot presentation of multi-dimensional data visual analysis, this paper proposes a visual analysis and processing method for high-speed train axle health monitoring, aiming at the problems of intensive rendering, visual mutation and trend prediction when drawing large data scatter plot. Firstly, a new method of the axle data fusion model is proposed in this paper, which can effectively clean the axle health monitoring data and construct the data acquisition and expression mode of axle temperature of high-speed train. Then, visualization of axle data and prediction of axle health trend provide a new analysis model for axle health monitoring. In addition, the visual analysis method of scatter density map data can eliminate the dependence of the original complex mechanical model, and can be used to analyze different working conditions and axle types. Compared with the existing axle health monitoring methods, this method has high accuracy and practicability.
机译：Axle是高速列车的重要组成部分。轴是连接火车的关键部件，这对火车安全产生了很大的影响。轴的健康监测对于火车的安全和平稳运行非常重要。轴健康检测是多因素耦合的复杂过程，这面临着健康模型构造的问题。从大数据视觉分析的角度来看，本文有助于人们找到高速铁路车轴监测大数据背后的信息，并对高速铁路轴操作的健康状况进行预测和分析。从目前的散点图呈现多维数据视觉分析的情况下，提出了一种用于高速列车轴健康监测的视觉分析和加工方法，旨在绘图时的密集渲染，视觉突变和趋势预测问题大数据散点图。首先，在本文中提出了一种新的轴数据融合模型的方法，其可以有效地清洁轴卫生监测数据并构建高速列车轴温度的数据采集和表达方式。然后，轴数据的可视化和轴健康趋势的预测为轴路健康监测提供了一种新的分析模型。另外，散射密度图数据的视觉分析方法可以消除原始复杂机械模型的依赖性，并且可用于分析不同的工作条件和轴类型。与现有的轴卫生监测方法相比，该方法具有高精度和实用性。

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  • 来源
    《Multimedia Tools and Applications》 |2020年第24期|16663-16681|共19页
  • 作者

    Kunlin Zhang; Jihui Xu; Huaiyu Xu; Ruidan Su;

  • 作者单位

    Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China University of Chinese Academy of Sciences Beijing China;

    Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China;

    Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China University of Chinese Academy of Sciences Beijing China;

    Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Scatter image; Density map; Axle; Kernel density estimation; High-speed train;

    机译：散射图像;密度图;轴;内核密度估计;高速火车;

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