Current wayside detection systems allow track operators to monitor
wheels and other aspects of the rail vehicle as they travel past an
instrumented site. For example, if dynamic impacts caused by
defective wheels on the track trigger a response exceeding a
pre-defined trigger, the operator will be alerted to inspect,
re-profile or potentially retire the wheel.
The aims of this project are to: a) review the Australian and
international trends in wayside detection systems and b) establish
an economic model to quantify the level of damage to rollingstock
and infrastructure from wheel-rail impact, relating the output from
Wheel Impact Monitors (WIM’s) to safety and economical limits
upon defect tolerances in wheels. The project was extended in 2005,
with the current research working to develop an impact load
spectrum for fatigue analysis of track and establish
engineering-based wheel management guidelines base on wheel impact
profiles.
The benefits of successful implementation of the work in the rail
industry include reduced costs of maintenance overall, including
reduced wheel grinding and track damage; reduced risk of derailment
and reduced fuel costs resulting from lower rolling friction. STEM
Partnerships evaluated the project in 2005 and found it had the
potential to deliver a risk-free-value of $136 million over the
next 15 years to the rail industry, and taking into account the
risks associated with delivering the technology, an estimated value
of $81 million.
Results to date:
- Completed literature review of international wayside detection
systems
- Conducted drop test rig experiments to determine track response to
impacts
- Developed algorithm to convert acceleration signals arising from
impact events on a track to its force-time history
- Instrumented section of track at Lara, Victoria and conducted field
testing to validate algorithm of impact force reconstruction
- Developed economic model using input from WIM output to assist
maintenance decisions
- Completed report on statistical distribution for wheel impact loads
recorded at test sites
Future outcomes:
- Impact load spectrum for fatigue analysis of track
- Engineering-based wheel management guidelines based on wheel impact
profile for use by industry.
Project Leader: Associate Professor WK Chiu (Monash)
Project Manager: Mr Mike Sowden (ARTC)
