English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Intelligent data-driven monitoring procedures hold enormous potential forensuring safe operation and optimal management of the railway infrastructure inthe face of increasing demands on cost and efficiency. Numerous studies haveshown that the track stiffness is one of the main parameters influencing theevolution of degradation that drives maintenance processes. As such, themeasurement of track stiffness is fundamental for characterizing theperformance of the track in terms of deterioration rate and noise emission.This can be achieved via low-cost On Board Monitoring (OBM) sensing systems(i.e., axle-box accelerometers) that are mounted on in-service trains andenable frequent, real-time monitoring of the railway infrastructure network.Acceleration-based stiffness indicators have seldom been considered inmonitoring applications. In this work, the use of a Vold-Kalman filter isproposed, for decomposing the signal into periodic wheel and track relatedexcitation--response pairs functions. We demonstrate that these components arein turn correlated to operational conditions, such as wheel out-of-roundnessand rail type. We further illustrate the relationship between the trackstiffness, the measured wheel-rail forces and the sleeper passage amplitude,which can ultimately serve as an indicator for predictive track maintenance andprediction of track durability.

Vold-Kalman Filter Order tracking of Axle Box Accelerations for Railway Stiffness Assessment