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Investigations to introduce the probability of detection method for ultrasonic inspection of hollow axles at Deutsche Bahn

机译:德斯克恩·鲍恩施工中空轴超声波检测检测方法概率研究

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The vast experience with the automated, ultrasonic system for the inspection of hollow railway axles used by Deutsche Bahn shows that much smaller flaws are detectable than required. This results in a number of false calls. False calls lead to unnecessary demounting and disassembling of wheelsets, which generates unnecessary additional costs. In order to adjust the sensitivity of the inspection system to reduce the number of false calls without compromising safety, the capability of the system to detect cracks needs to be comprehensively established. This capability can be quantified by using probability of detection (POD) curves for the system. The multi-parameter POD model makes it possible to include several factors that influence the crack detection in the analysis. The analysis presented in this paper shows that crack position, orientation, depth extension, and shape as well as the geometry of the axle all have influence on the ultrasonic response amplitude. For future work, calculation of the POD using multi-parameter POD model with these parameters is planned.
机译:通过德意志BAHN使用的空心铁路车道检查的自动化,超声波系统的丰富经验表明,比所需的缺陷更小。这导致了许多错误的呼叫。错误的要求导致不必要的拆卸和拆卸轮子,这产生了不必要的额外成本。为了调整检查系统的灵敏度,以减少错误呼叫的数量而不损害安全性,可以全面建立系统检测裂缝的能力。可以通过使用系统的检测概率(POD)曲线来量化该能力。多参数POD模型使得可以包括影响分析中裂纹检测的若干因素。本文提出的分析表明,裂缝位置,取向,深度延伸和形状以及轴的几何形状都对超声波响应幅度产生影响。为了将来的工作,计划使用具有这些参数的多参数POD模型的POD计算。

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