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

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Abstract

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.

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Authors and Affiliations

  1. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China

    Kunlin Zhang, Jihui Xu, Huaiyu Xu & Ruidan Su Ph.D

  2. University of Chinese Academy of Sciences, Beijing, China

    Kunlin Zhang, Jihui Xu & Huaiyu Xu

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  1. Kunlin Zhang
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  2. Jihui Xu
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  3. Huaiyu Xu
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  4. Ruidan Su Ph.D
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Correspondence to Huaiyu Xu or Ruidan Su Ph.D.

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Zhang, K., Xu, J., Xu, H. et al. Visual analytics towards axle health of high-speed train based on large-scale scatter image. Multimed Tools Appl 79, 16663–16681 (2020). https://doi.org/10.1007/s11042-019-08001-5

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