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首页> 外文期刊>Intelligent Transportation Systems, IEEE Transactions on >Automatic Detection of Squats in Railway Infrastructure
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Automatic Detection of Squats in Railway Infrastructure

机译：自动检测铁路基础设施中的蹲坐情况

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摘要

This paper presents an automatic method for detecting railway surface defects called “squats” using axle box acceleration (ABA) measurements on trains. The method is based on a series of research results from our group in the field of railway engineering that includes numerical simulations, the design of the ABA prototype, real-life implementation, and extensive field tests. We enhance the ABA signal by identifying the characteristic squat frequencies, using improved instrumentation for making measurements, and using advanced signal processing. The automatic detection algorithm for squats is based on wavelet spectrum analysis and determines the squat locations. The method was validated on the Groningen–Assen track in The Netherlands and accurately detected moderate and severe squats with a hit rate of 100%, with no false alarms. The methodology is also sensitive to small rail surface defects and enables the detection of squats at their earliest stage. The hit rate for small rail surface defects was 78%.
机译：本文提出了一种自动方法，该方法使用火车上的轴箱加速度（ABA）测量来检测称为“下蹲”的铁路表面缺陷。该方法基于我们小组在铁路工程领域的一系列研究结果，包括数值模拟，ABA原型的设计，实际实现和广泛的现场测试。我们通过识别特征下蹲频率，使用改进的仪器进行测量以及使用高级信号处理来增强ABA信号。蹲坐的自动检测算法基于小波频谱分析并确定蹲坐位置。该方法已在荷兰的Groningen-Assen轨道上进行了验证，可以准确检测到中度和重度蹲下，命中率为100％，没有误报。该方法对较小的钢轨表面缺陷也很敏感，并且可以在最早阶段检测下蹲现象。小轨表面缺陷的命中率为78％。

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