Curve squeal on the Stockholm metro Statistical analysis based on data collected by an onboard monitoring system

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Curve squeal is a high level tonal noise that is generated during curving of rail vehicles as a result of vibrations induced by the low rail (inner wheel) wheel–rail contact. Due to its large magnitude tonal components typically in the range up to 10 kHz, squeal is regarded to be the most annoying noise generated by the railway transport system. The mitigation of squeal noise is challenging and urgent as railway networks are often located in densely populated areas and rail-bound transportation is expected to become a backbone in the development of the future sustainable transportation system. The current study is based on noise data recorded by an onboard monitoring system during one year of traffic on the green metro line of the Stockholm metro. The influence of selected variables on the generation of curve squeal are investigated by a statistical assessment performed in two steps; (1) a screening analysis accounting for the entire green metro line with focus on variables related to track alignment (e.g. curve radius and track constructed inside or outside of tunnels) and environmental conditions (e.g. time of year and precipitation) and (2) a detailed analysis of the conditions that promote squeal generation at two selected short radius curves exposed to severe curve squeal. For the later a third-order logistic regression model is developed with air temperature, humidity and vehicle speed as predictor variables. The results clearly show the generation of curve squeal to become more frequent with decreasing curve radius. For the two curves studied in the logistic regression analysis, vehicle speed is found to be unimportant with respect to squeal generation. In this part of the study only the coefficient related to humidity shows a significant influence on the origin of curve squeal. The importance of environmental conditions is further emphasised by the observation that the occurrence of curve squeal decreases during precipitation.

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Squeal noise, curve squeal, logistic regression

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