We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
A linear Kalman filtering scheme for estimation of secondary vertical suspension of railway vehicles.
- Authors
Onat, Altan; Kılınç, Onur; Lata, Michael
- Abstract
Model based filtering is fast becoming a key instrument for maintenance and condition monitoring of railway vehicles. This study presents the use of linear Kalman filtering scheme to identify vertical secondary suspension of a railway vehicle by using the vertical vibrations of a vehicle due to vertical track irregularities. As well as the use of linear Kalman filtering scheme, a weighted least squares estimation is used to identify vertical secondary spring coefficient as a parameter by using residuals of the filter. In this investigation, a 7 degree of freedom dynamic model of ERRI B176 benchmark vehicle is considered. Unlike previous studies, to the authors’ knowledge, this research provides the simplest estimation scheme for identification of secondary vertical spring parameter and can be used to achieve a cost-effective condition based maintenance for railway vehicles.
- Subjects
KALMAN filtering; PARAMETER estimation; VIBRATION (Mechanics); SUSPENSION of railroad cars; SPRING constant (Physics)
- Publication
Vibroengineering Procedia, 2016, Vol 7, p124
- ISSN
2345-0533
- Publication type
Article