Measuring the speed of locomotives is important for train operation, especially in anti-slip control. A speed measurement method is proposed based on the correlation of vibration signals and the core process is to estimate the time shift of the windowed signals using the generalized cross-correlation (GCC) algorithm. A sensitivity analysis of the algorithm and suggested reasonable ranges for critical parameters are conducted. The effectiveness of the proposed method is demonstrated using both simulated and tested vibration signals, showing that it performs well under both constant and variable speed conditions. The proposed method had a maximum improvement in root-mean-square error (RMSE) of 2.72% compared to the measurement of the existing crosscorrelation (CC) algorithm. The proposed method is integrated into a heavy-haul train model with an anti-slip controller. Simulation results indicate that the method can accurately measure the locomotive speed when partial or all wheels slip.

Measurement of vehicle speed based on the GCC algorithm and its application in anti-slip control / Chen Q.; Ge X.; Shi Z.; Ling L.; Hu X.; Hu Y.; Wang K.. - In: MEASUREMENT. - ISSN 0263-2241. - ELETTRONICO. - 219:(2023), pp. 113298-113308. [10.1016/j.measurement.2023.113298]

Measurement of vehicle speed based on the GCC algorithm and its application in anti-slip control

Shi Z.;
2023

Abstract

Measuring the speed of locomotives is important for train operation, especially in anti-slip control. A speed measurement method is proposed based on the correlation of vibration signals and the core process is to estimate the time shift of the windowed signals using the generalized cross-correlation (GCC) algorithm. A sensitivity analysis of the algorithm and suggested reasonable ranges for critical parameters are conducted. The effectiveness of the proposed method is demonstrated using both simulated and tested vibration signals, showing that it performs well under both constant and variable speed conditions. The proposed method had a maximum improvement in root-mean-square error (RMSE) of 2.72% compared to the measurement of the existing crosscorrelation (CC) algorithm. The proposed method is integrated into a heavy-haul train model with an anti-slip controller. Simulation results indicate that the method can accurately measure the locomotive speed when partial or all wheels slip.
2023
219
113298
113308
Chen Q.; Ge X.; Shi Z.; Ling L.; Hu X.; Hu Y.; Wang K.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1330044
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
social impact