A method for diagnosing defects in wheel sets of rolling stock by magnetoinduction sensors
https://doi.org/10.46973/0201-727X_2023_3_177
Abstract
Increasing reliability and guaranteeing uninterrupted operation of the railway is an objection where its solution lies in the field of functionality of magnetic induction sensors. The results of this study were obtained on the basis of many years of experience in operating magnetic induction sensors in railway automation systems (RAS). An algorithm for identifying a wheel defect based on isolating a useful signal, as well as determining a signal corresponding to a certain type of defect, was studied. The results of the study made it possible to formulate a plan for the modernization of magnetic induction sensors with the prospect of combining them into a monitoring system that will continuously diagnose the technical condition of the rolling surface of rolling stock wheels when moving over the sensor. The introduction of this analysis technique will make it possible to diagnose flaws in railway wheel sets directly on the train route and guarantee a reduction in the accident rate on the railways of our country. Algorithms for signals corresponding to a specific defect are also being developed, and the implementation of developed software to expand the functionality of magnetic induction sensors is being developed.
About the Authors
V. A. Solomin
Rostov State Transport University (RSTU)
Russian Federation
Russian Federation
Vladimir A. Solomin - Chair «Electric Machines and Apparatuses», Doctor of Engineering Sciences, Professor.
V. V. Shtanke
Rostov State Transport University (RSTU)
Russian Federation
Russian Federation
Veronika V. Shtanke - Head of the Scientific and Innovation Center «Transport Safety».
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Review
For citations:
Solomin V.A., Shtanke V.V. A method for diagnosing defects in wheel sets of rolling stock by magnetoinduction sensors. Vestnik Rostovskogo Gosudarstvennogo Universiteta Putej Soobshcheniya. 2023;(3):177-187. (In Russ.) https://doi.org/10.46973/0201-727X_2023_3_177
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