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铁路车辆中空磨损车轮的剩余使用寿命估计通过车载随机振动基于车轮踏板深度估计

Ilias A Iliopoulos¹, John S Sakellariou¹

¹Stochastic Mechanical Systems & Automation (SMSA) Laboratory, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, Greece.

Sensors (Basel, Switzerland)

|January 23, 2024

概括

本研究引入了一种新的方法,用于使用振动数据来估计铁路轮的剩余使用寿命 (RULE). 该技术准确地预测了轮子的磨损和剩余的里程,提高了安全性和维护效率.

科学领域:

铁路工程铁路工程是指铁路工程.
状态监控状态监控
预测性维护是指预测性维护.

背景情况:

空洞磨损的铁路车轮构成了严重的安全风险.
准确估计剩余的使用寿命 (RULE) 对于有效的维护计划至关重要.
目前用于轮胎磨损评估的方法可能缺乏精度和实时功能.

研究的目的:

开发和验证一种用于估计空心磨损铁路轮的剩余使用寿命 (RULE) 的新方法.
为了利用车载的振动信号来准确地估计轮胎面积深度.
为了将估计的轮胎磨损与预测性维护的剩余里程相关联.

主要方法:

一种统计时间序列方法,采用数据驱动的随机函数组合模型.
模拟车辆动态在各种轮胎面积深度的车辆.
开发一个与车辆里程相关的轮胎流程深度演变功能.
通过基于Simpack的广泛蒙特卡洛模拟进行验证.

主要成果:

精确估计轮胎面积深度,平均绝对误差约为0.07毫米.
剩余的有用里程预测误差减少到大约3%.
与多重模型 (MM) 方法 (45.44%) 相比,提出的方法显示了明显更高的真实阳性率 (81.17%).

结论:

开发的统计时间序列方法提供了对空洞磨损铁路轮的准确可靠的剩余使用寿命估计.
这种方法为铁路车辆的预测性维护提供了有希望的进步.
该方法在现有技术上的优越性能突显了其在提高铁路安全和运营效率方面的潜力.

关键词:

加速度计的加速计是什么?空洞的磨损的车轮.在船上进行测量.铁路车辆铁路车辆铁路车辆剩余的使用寿命估计.统计时间序列方法.随机模型建模随机建模振动信号表示振动信号.

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