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In-service railway track condition monitoring by analysis of axle box accelerations for small to mid-size infrastructure operators

机译:通过分析小于中型基础设施运算符的轴箱加速度在 - 在 - 役铁路轨道状态监测

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About 50% of life-cycle-cost of railway tracks are caused by maintenance actions which are nowadays typically conducted within corrective maintenance schemes. The accelerating digitalization and development of low-cost sensors provide the chance especially for small infrastructure operators to introduce cost-effective track condition monitoring on a daily basis utilizing embedded sensors on their in-service vehicles. This will allow the challenging step forward from reactive corrections to proactive preventive maintenance actions to significantly reduce maintenance cost. We present the overall framework and first results of a prototype implementation of the complete system for quasi-continuous condition monitoring regarding short-wavelength (a few centimetre to a few meter) defects of railway tracks such as rail corrugation from the embedded sensor to the visualized data analysis result. We gather georeferenced triaxial axle box accelerations in the frequency range from 0.8 Hz to 8000 Hz by a prototype measurement system on a shunter locomotive operating on the railway network of Braunschweig inland harbour in Germany (total track length about 15 km). The prototype implementation in operational environment provides data of up to now four months of shunting operation to develop and evaluate data analysis algorithms. The acceleration sensor data is combined with further relevant data such as the digital map of the railway infrastructure and other operational data to be prepared for data analysis by our prototype implementation of a land-side data management system. We present results of the land-side data analysis chain including the track-selective georeferencing by multi-sensor-fusion, the extraction of relevant features from the axle box acceleration data for pattern recognition and the further intelligent data analysis to provide spatio-temporal information about track conditions. The obtained results are finally visualized for the infrastructure operator by the data management web-frontend.
机译:铁路轨道的大约50%的生命周期成本是由现在在校正维护方案中进行的维护动作引起的。低成本传感器的加速数字化和开发提供了尤其是小型基础设施运营商的机会,以便每天在其在职车辆上使用嵌入式传感器来引入经济高效的轨道状态监测。这将使挑战性的步骤从反应校正向主动预防性维护行动的主动预校正,以显着降低维护成本。我们介绍了全部系统的整体框架和第一个原型实施的原型实施,用于准连续状态监测关于短波长(几厘米到几米)的铁路轨道缺陷,例如从嵌入式传感器到可视化的铁路轨道的缺陷数据分析结果。在德国布劳伦奇港内陆港铁路网络上运行的工厂测量系统,我们在频率范围内收集0.8Hz至8000Hz的频率范围内的频率范围内的频率范围(总轨道长度约15公里)。操作环境中的原型实施提供了最多四个月的分流操作来开发和评估数据分析算法。加速度传感器数据与进一步的相关数据相结合,例如铁路基础设施的数字地图以及由我们的陆路数据管理系统的原型实施来准备用于数据分析的其他操作数据。我们呈现陆地数据分析链的结果,包括多传感器融合的轨道选择性地地理化,从轴箱加速数据提取相关特征,以实现模式识别和进一步的智能数据分析,以提供时空信息关于跟踪条件。最终通过数据管理网 - 前端为基础设施运营商可视化所获得的结果。

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