TY - JOUR
T1 - Evaluation of the influential parameters contributing to the reconstruction of railway wheel defect signals
AU - Alemi, Alireza
AU - Corman, Francesco
AU - Pang, Yusong
AU - Lodewijks, Gabriel
PY - 2019
Y1 - 2019
N2 - A wheel impact load detector is used to assess the condition of a railway wheel by measuring the dynamic forces generated by defects. This system normally measures the impact force at multiple points by exploiting multiple sensors to collect samples from different portions of the wheel circumference. The outputs of the sensors are used to estimate the dynamic force as the main indicator for detecting the presence of the defect. This method fails to identify the defect type and its severity. Recently, a data fusion method has been developed to reconstruct the wheel defect signal from the wheel–rail contact signals measured by multiple wayside sensors. The reconstructed defect signal can be influenced by different parameters such as train velocity, axle load, number of sensors, and wheel diameter. This paper aims to carry out a parametric study to investigate the influence of these parameters. For this purpose, VI-Rail is used to simulate the wheel–rail interaction and provide the required data. Then, the developed fusion method is exploited to reconstruct the defect signal from the simulated data. This study provides a detailed insight into the effects of the influential parameters by investigating the variation of the reconstructed defect signals.
AB - A wheel impact load detector is used to assess the condition of a railway wheel by measuring the dynamic forces generated by defects. This system normally measures the impact force at multiple points by exploiting multiple sensors to collect samples from different portions of the wheel circumference. The outputs of the sensors are used to estimate the dynamic force as the main indicator for detecting the presence of the defect. This method fails to identify the defect type and its severity. Recently, a data fusion method has been developed to reconstruct the wheel defect signal from the wheel–rail contact signals measured by multiple wayside sensors. The reconstructed defect signal can be influenced by different parameters such as train velocity, axle load, number of sensors, and wheel diameter. This paper aims to carry out a parametric study to investigate the influence of these parameters. For this purpose, VI-Rail is used to simulate the wheel–rail interaction and provide the required data. Then, the developed fusion method is exploited to reconstruct the defect signal from the simulated data. This study provides a detailed insight into the effects of the influential parameters by investigating the variation of the reconstructed defect signals.
KW - condition monitoring
KW - contact
KW - defect
KW - parametric study
KW - Railway wheel
KW - signal reconstruction
UR - http://www.scopus.com/inward/record.url?scp=85074610641&partnerID=8YFLogxK
U2 - 10.1177/0954409719882828
DO - 10.1177/0954409719882828
M3 - Article
AN - SCOPUS:85074610641
SN - 0954-4097
VL - 234 (2020)
SP - 1005
EP - 1016
JO - Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
JF - Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
IS - 9
ER -