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Modelling of the response of an ACFM sensor to rail and rail wheel RCF cracks

机译:ACFM传感器对钢轨和钢轨RCF裂纹的响应建模

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This paper discusses the relationship between ACFM signal and RCF defects in railway rails and wheels using an FEM model developed with COMSOL Multiphysics that has been verified for single and multiple RCF type cracks. The response to semi-elliptical defects of surface length 2 mm to 40 mm, and elliptical ratio 1:1 to 1.75:1, has been simulated and it is shown that the ACFM signal is most sensitive to, and therefore able to accurately size, RCF defects < 20 mm surface length (classified by Network Rail on rails as light-moderate). The sensitivity to sensor lift off and sensor angle relative to crack angle, which is of importance for high-speed and fixed sensor systems, is presented for a semi-elliptical crack. For a complex defect extending into the rail beyond the surface breaking component (a morphology that can be seen for moderate, heavy or severe RCF cracks in rail), the effect of using a sizing algorithm based on semi-elliptical shapes is quantified; it is shown that the defect would be undersized by 34.4% using this approach. Finally, the ACFM response to clusters of 4 semi-elliptical defects with inter-crack spacings of between 1 mm and 19 mm is presented. It is shown that closely spaced cracks give a large signal that could be interpreted as one large defect; this effect is quantified.
机译:本文使用COMSOL Multiphysics开发的FEM模型讨论了ACFM信号与铁路轨道和车轮中RCF缺陷之间的关系,该模型已针对单个和多个RCF型裂纹进行了验证。模拟了对表面长度2 mm至40 mm的椭圆形比率为1:1至1.75:1的半椭圆形缺陷的响应,结果表明ACFM信号对尺寸最敏感,因此能够精确确定尺寸, RCF缺陷<20毫米表面长度(按导轨上的Network Rail分类为轻度中等)。对于半椭圆形裂纹,提出了对传感器提起的灵敏度以及相对于裂纹角度的传感器角度的敏感性,这对于高速和固定传感器系统而言非常重要。对于延伸到钢轨中超出表面破坏成分的复杂缺陷(在钢轨中出现中度,重度或严重RCF裂纹的形态而言),使用基于半椭圆形状的尺寸调整算法的效果得到了量化;结果表明,使用这种方法可以将缺陷缩小34.4%。最后,提出了ACFM对裂纹间距在1mm至19mm之间的4个半椭圆形缺陷簇的响应。结果表明,紧密排列的裂纹会产生较大的信号,可以解释为一个较大的缺陷。这种影响是可以量化的。

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