Fault detection of damper in railway vehicle suspension based on the cross-correlation analysis of bogie accelerations

Abstract

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.

Experimental Analysis of Vertical Vibrations of a Railway Bogie

“…The RMS acceleration is also marked on the diagrams. In all the cases presented, it is observed that the RMS The accelerometers were mounted on a side of the bogie as follows: one accelerometer on each axle box and one accelerometer on the bogie frame against each axle (Figures 2 and 3) [30][31].…”

“…Recent studies, based on the measured data or numerical simulations, have shown that the vehicle dynamic response is correlated with the track irregularities [10,13,[27][28][29], which creates the premises of developing certain monitoring methods of track quality or the vehicle condition [30]. The correlation method has been used to highlight the connection between the lateral and vertical axle box acceleration and differently processed track geometry parameters,…”

Deep learning-based fault diagnostic network of high-speed train secondary suspension systems for immunity to track irregularities and wheel wear

“…The data-driven approach does not rely on vehicle simulation models but requires historical tracking data and prior training. As shown in Table 1, the data-driven approaches with different strategies for FD/I of railway vehicle suspensions over the past two decades can be mainly classified into four sub-categories: (1) (1) SM-based [29][30][31][32][33][34][35]: A classical SM-based approach used in RVSFD is based on the cross-correlation function. In [29], the cross-correlation function between the accelerations of two bogies was applied to determine the health conditions of vehicle suspension systems.…”

Study on the Effect of Damping Asymmetry of the Vertical Suspension on the Railway Bogie Vibrations

“…The issue of the damping asymmetry of the railway vehicles suspension has been mainly addressed from the perspective of detecting and identifying the suspension defects, a technique known as condition monitoring [5][6][7][8][9][10]. Many research studies in this regard is being developed using model-based methods where the asymmetry of the suspension damping is included, such as interacting multiple-model algorithm [11,12], functional model method [13], evaluating estimation residuals [14], system dynamic interactions method [15][16][17], cross-correlation analysis based method [18][19][20].…”