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Prediction of RCF clustered cracks dimensions using an ACFM sensor and influence of crack length and vertical angle

机译:使用ACFM传感器预测RCF聚类裂缝尺寸及裂缝长度和垂直角度的影响

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摘要

Rolling contact fatigue (RCF) cracks are the predominant reason for rail grinding maintenance and replacement on all types of railway system, as they can potentially cause rail break if not removed. To avoid excessive material removal, accurate crack sizing is required. Alternating current field measurement has been used as an electromagnetic method for RCF crack sizing, incorporating with modelling results for single RCF cracks with large vertical angles (>30 degrees). No study using this knowledge to size shallow angled crack clusters has yet been reported. A novel method, the pocket length compensation method, is proposed to determine the length and depth of RCF cracks with shallow vertical angles. For shallow crack clusters, vertical angle predictions are close to the measured values with a deviation of less than 13.6%. Errors in crack pocket length prediction are greatly reduced when the pocket length compensation was included. The predicted vertical depth using the approach developed for clustered angled cracks is accurate with errors <8.3%, which compares to errors of up to 60% if the single RCF crack approach is used and errors of up to 21.4% if a non-compensated prediction for crack clusters is used.
机译:滚动接触疲劳(RCF)裂缝是轨道磨削维护和替代所有类型的铁路系统的主要原因,因为如果没有拆卸,它们可能会导致轨道断裂。为避免过度的材料去除,需要精确的裂缝尺寸。交替的电流场测量已被用作RCF裂缝尺寸的电磁方法,其中包含具有大垂直角度(> 30度)的单个RCF裂缝的建模结果。尚未报告使用这种知识的研究尚未报告浅浅浅角度簇。一种新的方法,提出了袋长补偿方法,以确定具有浅垂直角度的RCF裂缝的长度和深度。对于浅裂缝簇,垂直角度预测接近测量值,偏差小于13.6%。当包括口袋长度补偿时,裂缝口袋长度预测中的误差会大大降低。使用为聚类成角度裂缝开发的方法的预测垂直深度具有误差<8.3%,如果使用单个RCF裂纹方法,则比较60%的误差,如果不补偿预测,则最高可达21.4%的误差用于裂缝簇。

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