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Fault detection of damper in railway vehicle suspension based on the cross-correlation analysis of bogie accelerations
Author(s) -
Mădălina Dumitriu
Publication year - 2019
Publication title -
mechanics and industry
Language(s) - English
Resource type - Journals
eISSN - 2257-7777
pISSN - 2257-7750
DOI - 10.1051/meca/2018051
Subject(s) - bogie , damper , suspension (topology) , structural engineering , track (disk drive) , reliability (semiconductor) , axle , automotive engineering , fault (geology) , acceleration , computer science , engineering , control theory (sociology) , mathematics , mechanical engineering , physics , power (physics) , control (management) , classical mechanics , quantum mechanics , artificial intelligence , homotopy , seismology , pure mathematics , geology
Nowadays, the condition-based maintenance is associated more and more with railway transport to improve the safety, availability, reliability and capacity of this transport system, and to reduce life cycle costs for the railway vehicles. The condition-based maintenance requires that vehicle components are replaced based on their real condition, which implies the fault detection and isolation during the train's operation. The paper proposes a method to detect the failure of the damper in the primary suspension of the rail vehicle, based on the analysis of cross-correlation of the vertical accelerations measured on the bogie frame against the two axles. The numerical simulations and experimental results show a very good correlation between the bogie accelerations when the dampers are in a normal operation condition. This thing is shown based on the values of the cross-correlation coefficient (CCC) of the bogie accelerations. The failure in a damper can be detected by the decrease of the CCC of the bogie accelerations, a confirmed fact in the results derived from numerical simulations. The proposed method has more advantages, namely, it is a signal-based method and hence does not require a complex mathematical modelling of the vehicle-track system and knowledge of its parameters or of the external conditions; the method makes relative comparisons between measurements and hence reduces the effect of the factors that influence outputs; the method can be also extended for the secondary suspension; the method can be easily implemented on any type of bogie.

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