Title: Data driven condition assessment of railway infrastructure
Abstract: The Swiss Federal Railways (SBB) pursue a long-term sustainable maintenance and renewal strategy of their infrastructure, which relies on condition assessment via use of specialized monitoring vehicles, detailed inventory data, Geographic Information System (GIS) data and local inspections. The goal is to optimize maintenance and renewals for ensuring resilience, while minimizing life-cycle costs. The durability of the railway track, as well as its renewal costs are strongly dependent on the condition of certain components, such as the substructure. However, the condition of the substructure is most often unknown due to lack of accessibility. In this work, we analyze of inventory, load and measurements data over the track life to identify the state of the substructure by looking for traces of degradation on the available data. The analysis is validated via comparison to the renewal decisions, as recorded on annual track renewal plans based on geotechnical inspections. Two energy-based indicators are extracted by a space-frequency analysis of the longitudinal level measurements of the monitoring vehicle. The time variance of these characteristics is statistically modeled. From these findings, we stochastically estimate the probability of the necessity of a substructure renewal at each track location in function these quantities.
Publication Year: 2021
Publication Date: 2021-03-24
Language: en
Type: book-chapter
Indexed In: ['crossref']
Access and Citation
Cited By Count: 6
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