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Fault detection method for railway wheel flat using an adaptive multiscale morphological filter

机译：基于自适应多尺度形态学滤波器的铁路轮毂故障检测方法

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摘要

This study explores the capacity of the morphology analysis for railway wheel flat fault detection. A dynamic model of vehicle systems with 56 degrees of freedom was set up along with a wheel flat model to calculate the dynamic responses of axle box. The vehicle axle box vibration signal is complicated because it not only contains the information of wheel defect, but also includes track condition information. Thus, how to extract the influential features of wheels from strong background noise effectively is a typical key issue for railway wheel fault detection. In this paper, an algorithm for adaptive multiscale morphological filtering (AMMF) was proposed, and its effect was evaluated by a simulated signal. And then this algorithm was employed to study the axle box vibration caused by wheel flats, as well as the influence of track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method was verified by bench testing. Research results demonstrate that the AMMF extracts the influential characteristic of axle box vibration signals effectively and can diagnose wheel flat faults in real time.
机译：这项研究探索了形态学分析在铁路车轮漏气故障检测中的能力。建立了一个具有56个自由度的车辆系统动力学模型以及一个轮距模型，以计算轴箱的动态响应。车辆轴箱振动信号很复杂，因为它不仅包含车轮缺陷信息，而且还包含轨道状况信息。因此，如何有效地从强烈的背景噪声中提取出车轮的影响特征是铁路车轮故障检测的典型关键问题。提出了一种自适应多尺度形态学滤波算法，并通过仿真信号对其效果进行了评估。然后，采用该算法研究了车轮漏气引起的轴箱振动，以及履带不平顺和车辆行驶速度对诊断结果的影响。最后，通过台架试验验证了该方法的有效性。研究结果表明，AMMF能够有效地提取轴箱振动信号的影响特征，并且能够实时诊断车轮漏气故障。

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  • 来源
    《Mechanical systems and signal processing》 |2017年第ptaa期|642-658|共17页
  • 作者

    Yifan Li; MingJ. Zuo; Jianhui Lin; Jianxin Liu;

  • 作者单位

    School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China,Department of Mechanical Engineering, University of Alberta, Edmonton, Canada T6G 1H9;

    School of Mechatronics Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China,Department of Mechanical Engineering, University of Alberta, Edmonton, Canada T6G 1H9;

    Traction Power State Key Lab, Southwest Jiaotong University, Chengdu 610031, China;

    Traction Power State Key Lab, Southwest Jiaotong University, Chengdu 610031, China;

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  • 正文语种 eng
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  • 关键词

    Wheel flat; Fault detection; Mathematical morphology; Adaptive; Multiscale morphological filter;

    机译：轮平;故障检测;数学形态自适应多尺度形态学过滤器;

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