Fatigue Analysis on Four Months of Data on a Steel Railway Bridge: Event Detection and Train Features’ Effect on Fatigue Damage

Bridges are critical infrastructures subjected to cyclic loading and
require fatigue monitoring to prevent high maintenance costs due to fatigue
failure. This paper, part of OWI-lab’s research activities within the SafeLife-
Infrabel project, presents a fatigue survey on four months of strain measurements
of a steel railway bridge in Belgium, comprising 98 Fiber Bragg Gratings
(FBGs). This study aims to develop a data-driven case/event detection scheme
including measurements and operational data (e.g., train type and passage time).
The first objective is to develop a Python package to separate the events by
automatically selecting the train passage events from the strain time series to
analyze them and also reduce the dataset size. Over the studied period, a total of
5000 events were detected. Then, the available operational data is complemented
with properties estimated from the strain measurements, including the
axle number, speed, and direction. Finally, the relation between the fatigue
damage and different train features is studied by calculating the attributed fatigue
damage using the Rainflow cycle counting method and the Palmgren-Miner
rule. A notable damage difference existed between freight and passenger trains.
In addition, the damage difference between loaded and empty freight trains was
completely distinguishable, while the effect of occupancy was not very visible in
passenger trains. Axle number had the highest impact among the passenger
trains and had linear relation with damage. Also, the difference in fatigue
damage between various types of passenger trains was less distinctive. Finally,
the speed and direction affected the damage very slightly.