A Novel Description Method for Track Irregularity Evolution
Peng Xu, Rengkui Liu, Futian Wang and 2 more
International Journal of Computational Intelligence Systems · 2011
doi:10.2991/ijcis.2011.4.6.29 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
Track Irregularity has a significant influence on the safety of train operation. Due to the fact that the extremely large number of factors affect track irregularity it is challenging to find a concise yet effective mathematical method to describe the evolution of track irregularity. In this paper, inspection data generated by GJ-4 track inspection cars from Jinan Railway Bureau in China were analyzed to identify the characteristics of track irregularity changes common to different mileage points. Based on these characteristics, a multi-stage linear fitting model to describe the pattern of track irregularity evolution over time was developed. The availability of new inspection data will make the model revise itself. In this sense, the model is a machine learning model. Finally, inspection data from the Beijing-Shanghai Railway Line (Jing-Hu Line) were used to verify the model.
Abstract licence: CC BY-NC-ND
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.