کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
699564 | 890777 | 2007 | 13 صفحه PDF | دانلود رایگان |

This paper investigates the problem of parameter estimation for railway vehicle suspensions so as to provide information to support condition-based (instead of calendar-based) maintenance. A simplified plan view railway vehicle dynamical model is derived and a newly developed Rao–Blackwellized particle filter (RBPF) based method is used for parameter estimation. Computer simulations are carried out to assess and compare the performance of parameter estimation with different sensor configurations as well as the robustness with respect to the uncertainty in the statistics of the random track inputs. The method is then verified practically using real test data from a Coradia Class 175 railway vehicle with only bogie and body mounted sensors, and some preliminary results are presented.
Journal: Control Engineering Practice - Volume 15, Issue 1, January 2007, Pages 43–55