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Axlebox accelerations: Their acquisition and time-frequency characterisation for railway track monitoring purposes

机译:轴箱加速度:其采集和时频特性用于铁路轨道监控

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Railway track maintenance is becoming a real challenge for Railway Engineers due to the need of meeting increasingly high quality requirements by means of cost-effective procedures. Frequently, this can be only achieved by implementing some technological developments from other fields into the railway sector, such as Digital Signal Processing. Indeed, the present work delves into data acquisition and processing techniques in order to enhance track surveying processes. For this purpose, run tests on the Metropolitan Rail Network of Valencia (Spain) were carried out, and axlebox accelerations were gathered and analysed in different ways. The results determined the optimal sampling and filtering frequencies as well as the location of accelerometers along the train. Furthermore, by means of spectral analysis and time-frequency representations, diverse track defects, track singularities and vibration modes can be clearly identified. It is shown how, with a Hamming time window of 0.5 s and an overlapping of 95%, a wide set of track defects can be detected, without the need of complementary analyses. These values yield the best results as they are a good compromise between time and frequency resolution and allow for appropriate pattern recognition of the corresponding track singularities and resonant frequencies. (C) 2016 Elsevier Ltd. All rights reserved.
机译:由于需要通过具有成本效益的程序来满足越来越高的质量要求,铁路轨道维护已成为铁路工程师的真正挑战。通常,这只能通过在其他领域实现一些铁路领域的技术发展来实现,例如数字信号处理。实际上,当前的工作深入研究了数据采集和处理技术,以增强航迹测量过程。为此,在瓦伦西亚(西班牙)的大都市铁路网上进行了运行测试,并以不同的方式收集并分析了轴箱加速度。结果确定了最佳采样和滤波频率以及加速度计在火车上的位置。此外,借助频谱分析和时频表示,可以清楚地识别出各种轨道缺陷,轨道奇异点和振动模式。它显示了如何在0.5 s的汉明时间窗口和95%的重叠率下检测到广泛的轨道缺陷,而无需进行补充分析。这些值可产生最佳结果,因为它们是时间和频率分辨率之间的良好折衷,并允许对相应的磁道奇点和谐振频率进行适当的模式识别。 (C)2016 Elsevier Ltd.保留所有权利。

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