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An on-board detection framework for polygon wear of railway wheel based on vibration acceleration of axle-box

机译:基于轴箱振动加速的铁路多边形磨损的板载检测框架

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摘要

The polygon wear of railway wheel (PWRW) is a wear fault that is ubiquitous in railway vehicles. PWRW can induce a strong periodic excitation to both vehicle and track, which not only decreases passenger comfort but also is detrimental to the operational reliability and safety. Both the degree and the order of PWRW are important parameters used to quantify the fault. Because the fault-related components distribute at a wide range in the frequency domain, it is easy to alias with some radiated vibrations from vehicle and track components, which makes the on-board detection for both parameters of PWRW very difficult. To address the practical engineering problem, this paper proposes a detection framework based on the angle domain synchronous averaging technique (ADSAT). The detection method employs the vertical axle-box vibration acceleration (ABVA), which is easy to obtain and can also be used to monitor the conditions of axle-box bearings. The paper compares the proposed and traditional methods. The results reveal that the proposed method not only achieves the order detection which the traditional method cannot, but also mitigates the influence of background noise. The feasibility and effectiveness of the proposed method to improve the detection accuracy of PWRW is demonstrated through simulation and real field investigations.
机译:铁路轮(PWRW)的多边形磨损是铁路车辆中无处不在的磨损故障。 PWRW可以向车辆和轨道引起强烈的周期性激励,这不仅降低了乘客舒适性,而且对操作的可靠性和安全性也有害。 PWRW的程度和顺序都是用于量化故障的重要参数。由于故障相关的组件在频域中的宽范围内分布,因此易于别名,车辆和轨道部件具有一些辐射振动,这使得载体检测对于PWRW的两个参数非常困难。为了解决实际工程问题,本文提出了一种基于角度域同步平均技术(ADSAT)的检测框架。检测方法采用垂直轴箱振动加速度(ABVA),易于获得,也可用于监测轴箱轴承的条件。本文比较了提议和传统方法。结果表明,该方法不仅达到了传统方法不能,而且还减轻了背景噪声的影响。通过模拟和实地调查证明了提高PWRW检测精度的提出方法的可行性和有效性。

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