In this paper a method is proposed to monitor the degradation of the performances of a railway bogie and to detect the incipient instability of the vehicle well in advance the limit values of the lateral acceleration are reached. The same condition based monitoring technique can also be used to detect the presence of faults in some bogie components critical to vehicle stability, and to resolve between different fault types (e.g. wear of the wheel profile, reduction of anti yaw damper characteristic, degradation of the primary suspension parameters). The method is based on the analysis of the lateral accelerations of the bogie frame using the random decrement technique (RTD) to extract the free response of the bogie. The output of the RTD algorithm is then analysed in time domain using the Prony method to identify the characteristic exponent of the systems, eventually allowing to define the stability margin of the bogie together with other characteristic parameters such as bogie natural frequencies and the y/ ratio between the lateral and yaw components of its mode shape. The trend with time of these parameters is used to monitor the degradation of bogie performance, and the results can be used to drive preventive maintenance actions.

Early Instability Detection for High Speed Railway Bogies

BRUNI, STEFANO;ALFI, STEFANO
2010-01-01

Abstract

In this paper a method is proposed to monitor the degradation of the performances of a railway bogie and to detect the incipient instability of the vehicle well in advance the limit values of the lateral acceleration are reached. The same condition based monitoring technique can also be used to detect the presence of faults in some bogie components critical to vehicle stability, and to resolve between different fault types (e.g. wear of the wheel profile, reduction of anti yaw damper characteristic, degradation of the primary suspension parameters). The method is based on the analysis of the lateral accelerations of the bogie frame using the random decrement technique (RTD) to extract the free response of the bogie. The output of the RTD algorithm is then analysed in time domain using the Prony method to identify the characteristic exponent of the systems, eventually allowing to define the stability margin of the bogie together with other characteristic parameters such as bogie natural frequencies and the y/ ratio between the lateral and yaw components of its mode shape. The trend with time of these parameters is used to monitor the degradation of bogie performance, and the results can be used to drive preventive maintenance actions.
2010
Rail vehicle dynamics; Hunting instability; Critical speed; Condition based monitoring; Fault detection
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/580883
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