Estimation of lateral track irregularity using a Kalman filter. Experimental validation

Muñoz, Sergio; Ros, Javier; Urda, Pedro; Escalona, José L.

doi:10.1016/j.jsv.2021.116122

Cited by 18 publications

(7 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…[27] proposed three different model-based methods to estimate both lateral track alignment and cross-level irregularities: 1) pseudo-inversion of the vehicles frequency response function (FRF) matrix, 2) unknown input estimation using a deterministic observer and 3) unknown input estimation using a linear Kalman filter as a stochastic observer. In [28] Muñoz et. al.…”

Section: Gnssmentioning

confidence: 99%

Estimation of the trajectory and attitude of railway vehicles using inertial sensors with application to track geometry measurement

González-Carbajal¹,

Urda²,

Muñoz³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

This paper describes a novel method for the estimation of the trajectory curve and orientation of a rigid body moving along a railway track. Compared to other recent developments in the literature, the presented approach has the significant advantage of tracking the position and orientation of a railway vehicle using inertial sensors only (a 3D gyroscope and a 3D accelerometer), excluding global position sensors (GNSS or total station) and also excluding global orientation sensors (magnetometers or inclinometers).The algorithm is based on a kinematic model of the relative motion of the body with respect to the track. This kinematic model is used as the system equations of a Kalman filter algorithm that includes in the state vector the coordinates used to define the position and orientation of the body. Two different Kalman filter approaches are described. In the first one, the position and orientation are calculated independently. In the second one, both position and orientation are calculated as a coupled problem. Crucial to the success of the results of the Kalman filters is the use of the correct covariance matrices associated with the system process and the measurements. Again, two approaches are used for the estimation of the covariance matrices. One is based on the use of experimental results with a known output. The other one is based on constrained maximum likelihood estimation. The calculated trajectory and orientation are applied in this research to the problem of track geometry measurement. This is a very demanding application because the measurement of track irregularities requires millimetric accuracy. A scale track with known design geometry and irregularities is used to conduct experiments for tuning and evaluating the quality of the output of the algorithm. Results show that the developed algorithm is accurate enough for this application. They also show that, using either of the two proposed Kalman filtering approaches, the constrained maximum likelihood method for the estimation of the covariance matrices performs similarly to the known-output method. This is very convenient because it allows a straightforward application of the observation model in different scenarios.

show abstract

Section: Gnssmentioning

confidence: 99%

Estimation of the trajectory and attitude of railway vehicles using inertial sensors with application to track geometry measurement

González-Carbajal¹,

Urda²,

Muñoz³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…La introducción de dichas mediciones virtuales se realiza a efectos de mejora en el funcionamiento del filtro. Este efecto ha sido previamente comprobado en [21]. El vector de mediciones quedaría expresado en la siguiente forma: Título en el idioma en que se presenta el artículo (debe ser igual al del encabezado) Donde acm hace referencia a la medida del acelerómetro, gyr a la del giróscopo y 𝜉 𝑔𝑣 𝑚𝑒𝑎𝑠 representa la medida de la variación de ancho de vía realizada por el LVDT instalado en el vehículo.…”

Section: Filtro De Kalmanunclassified

Metodología experimental para la medición automática de irregularidades de vía

2022

Congreso Iberoamericano De Ingeniería Mecánica-Cibim 2022

View full text Add to dashboard Cite

Este trabajo presenta el desarrollo de una metodología experimental para la medición de irregularidades de vía utilizando un sistema automatizado basado en medidas inerciales y el empleo de técnicas de filtro de Kalman. Dicha metodología ha sido validada experimentalmente en un trazado ferroviario a escala 1:10 y un vehículo auscultador de vías también a escala reducida. Los resultados obtenidos demuestran que mediante el método empleado se puede llevar a cabo una auscultación geométrica del trazado ferroviario de forma rápida y precisa, obteniendo como resultado las cuatro irregularidades fundamentales de la vía. El sistema propuesto ha sido además implementado en un ordenador en tiempo real embarcado en el vehículo, con el que se prueba el funcionamiento en tiempo real del método propuesto.

show abstract

“…The presented concepts are potentially useful for the development of the systems for the track lateral geometry monitoring. The work [32] shows the development of a model-based methodology for the estimation of lateral track irregularities from measurements from different sensors mounted on an in-service vehicle. The proposed methodology is based on the Kalman filtering technique, through the use of a highly simplified linear dynamic model of a bogie, capable of capturing the most relevant lateral dynamic behavior of the entire vehicle.…”

Section: Review Of the Current Studiesmentioning

confidence: 99%

Monitoring and Evaluation of the Lateral Stability of CWR Track

Atapin

Bondarenko

Sysyn

et al. 2021

J Fail. Anal. and Preven.

View full text Add to dashboard Cite

Continuous welded rail (CWR) track has great advantages of low-cost maintenance, environmental influence, and ride comfort. However, the CWR track is subjected to the longitudinal stresses in rails due to temperature influence as well the inhomogeneous stress accumulation due to train loadings. The stresses cause the accelerated track lateral irregularity accumulation that without timely maintenance can cause track buckling. The present paper present a method of the CWR track lateral stability estimation during its lifecycle using the track geometry monitoring information from the track measurement cars. The methods proposes a systematic approach of track stability evaluation based on multiple criteria of track stability evaluation. It takes into account the lateral resistance of the track, actual temperatures, and the lateral geometry condition of the track. The presented case study of a half-year track geometry monitoring and the track stability evaluation in a track curve shows the practical possibility of the recent detection of the track sections with low lateral stability and buckling prevention.

show abstract

Estimation of lateral track irregularity using a Kalman filter. Experimental validation

Cited by 18 publications

References 16 publications

Estimation of the trajectory and attitude of railway vehicles using inertial sensors with application to track geometry measurement

Estimation of the trajectory and attitude of railway vehicles using inertial sensors with application to track geometry measurement

Metodología experimental para la medición automática de irregularidades de vía

Monitoring and Evaluation of the Lateral Stability of CWR Track

Contact Info

Product

Resources

About