Railway Condition Monitoring
Submitting Institution
University of BirminghamUnit of Assessment
Electrical and Electronic Engineering, Metallurgy and MaterialsSummary Impact Type
TechnologicalResearch Subject Area(s)
Mathematical Sciences: Applied Mathematics
Information and Computing Sciences: Computer Software
Summary of the impact
The Railway Systems Group develops state-of-the-art condition monitoring
and instrumentation
systems that identify system faults before they degrade into failures that
cause passenger
disruption. The key impacts of the Railway Systems Group lie in the
following areas:
- Detection and diagnosis of faults in railway assets (e.g. point
machines, track circuits,
vehicle components);
- Collection and analysis of track data from in-service railway vehicles
(e.g. conductor shoe
monitoring, track geometry, non-destructive testing);
- Energy monitoring to quantify loses in the railway power system;
- Assessing the effectiveness of winter weather mitigation solutions.
Examples of direct quantifiable impact are a reduction of over 60,000
minutes in train delays over
the last one year period through monitoring of 5,600 railway point
machines (the cost to Network
Rail of delays is between £20/min to £160/min). Also, the deployment of an
award winning
conductor shoe monitoring system, which has resulted in an estimated
savings of 12,150 minutes.
Expert advice and practical prototypes have been through active contracts
from railway companies
totalling £4.2M. This includes an influence in the £7 billion successful
order from the Department
for Transport to Hitachi for new trains, energy saving strategies reported
by the Office of the Rail
Regulator and evidence to the Transport Select Committee on winter
operations.
These have been achieved by working extensively with the British and
international railway
industries in the area of condition monitoring and bespoke instrumentation
systems that support an
improvement in the dependability of rail travel.
Underpinning research
The Railway Systems Group at Birmingham is the only Electrical and
Electronic based railway
research group in the UK. The group was founded in the 1970's. The group
holds a strong
international reputation for undertaking industrially focussed research.
The research in railway condition monitoring has been carried out by
three academic staff (C
Roberts, Professor of Railways System Engineering, 1997-, Dr S Hillmansen,
Senior Lecturer,
2006- , Dr E Stewart, Birmingham Research Fellow, 2007-). Since 2008, 20
PhD students have
worked (or are currently working) in this area. The active research
contracts over this period total
over £7M, which includes involvement in 9 European Framework projects, 3
EPSRC projects
(including a programme grant), a large ERDF initiative and numerous
industrially funded projects.
Since 2008, the group has published over 50 papers in international peer
reviewed journals.
In addition to funding from the UK, railway condition monitoring research
has been supported by
funding and collaborations from Hitachi (Japan), Central Railways (Japan),
Deutsche Bahn
(Germany), Alstom (France), Trafikverket (Sweden) and REFER (Portugal).
Professor Roberts, who leads the group, has excellent research esteem.
For example he is
founder and chair of the biennial IET International Conference in Railway
Condition Monitoring
(since 2003). In 2008 Professor Roberts gave a keynote address at the
International Federation of
Automatic Control (IFAC) SAFEPROCESS conference detailing the significant
academic progress
and industrial take-up of railway condition monitoring, which was followed
in 2013 by a keynote
address at the IFAC Workshop on Advances in Control and Automation Theory
for Transportation.
In 2011 Professor Roberts was asked to give the IMechE Railway Division
Annual Research
Lecture on his work in the field of railway condition monitoring. In 2013
he developed and co-chaired
the 1st IEEE International Conference on Intelligent Rail
Transportation in Beijing.
Research at Birmingham has focused on:
(1) The development of sophisticated bespoke instrumentation that
is designed to be resilient to
the harsh and variable environments of the railway. The instrumentation,
based on distributed
embedded system design, has been installed on railways throughout the
world (UK, Portugal,
Germany, Sweden, Japan). Research focuses on solutions that are able to
work in-service without
human intervention. A current project funded by the EPSRC, as part of the
Track 21 Programme
Grant, has the objective to advise on appropriate instrumentation systems
for the proposed High
Speed 2 railway line as well as in other key projects. Other work is
developing distributed acoustic
monitoring system to be used by Hitachi to detect bearing faults on its £7
billion Intercity Express
Programme trains due to begin operation in the UK between 2016-2018. Some
of the technology
developed by the group for railways has been applied to wind turbines in
Greece [3.1];
(2) The development of robust data processing algorithms that are
able to process the data
collected from the instrumentation in close to real-time in order to
detect incipient faults in systems,
or at particular locations on the track. In recent years research has
moved on to fault diagnosis and
prognosis, and this work has begun to be used in the field, most notably
as part of Network Rail's
Intelligent Infrastructure programme. For use in railway environments,
where system, climate and
usage varies, it has been shown that conventional condition monitoring
approaches are not
suitable. The group has pioneered and demonstrated under real life
condition the benefits of
combining quantitative and qualitative approaches. Initial work focused on
algorithms for the
condition monitoring of point machines [3.2]. This work was further
enhanced and applied to track
circuits [3.3], track geometry measurement using bogie mounted inertial
measurements systems
[3.4], acoustic emission sensors for crack growth monitoring [3.5] and
non-destructive testing
evaluation systems for rail and wheelset monitoring [3.6];
(3) In parallel with this work, collaborative research with
Network Rail has been undertaken to
develop clear, engineering led business cases to support the roll-out of
condition monitoring [3.7].
This work has been important to Network Rail proceeding with its
Intelligent Infrastructure
programme. Additional research has also been undertaken to use
instrumentation to help evaluate
the effectives of subsystems, particularly to evaluate performance in
winter weather. Through this
research the University has developed standard test procedure to help
Network Rail evaluate the
effectiveness of winter mitigation measures.
References to the research
The outputs that best indicate the quality of the underpinning research
are 3.2, 3.3 and 3.4.
1. M Entezami, S Hillmansen, P Weston, M Papaelias, 2012. Fault detection
and diagnosis within a
wind turbine mechanical braking system using condition monitoring,
Renewable Energy, 47, 175-182.
doi:10.1016/j.renene.2012.04.031
2. C Roberts, CJ Goodman, HP Dassanayake, N Lehrasab. 2002. Distributed
quantitative and
qualitative fault diagnosis: Railway junction case study, Control Eng.
Practice, 10(4), 419-429. doi:
10.1016/S0967-0661(01)00159-9
3. J Chen, C Roberts, P Weston, 2008. Fault diagnosis for railway track
circuits using neuro-fuzzy
systems, Control Engineering Practice, 16(5), 585-596.
doi:10.1016/j.conengprac.2007.06.007
4. P Weston, CS Ling, C Roberts, C Goodman, P Li, R Goodall, 2007.
Monitoring vertical track
irregularity from in-service railway vehicles, Proceedings of the IMechE:
Part F — Journal of Rail
and Rapid Transit, 221(1), 75-88. doi: 10.1243/0954409JRRT65
5. A Kostryzhev, C Davis, C Roberts, 2012. Detection of crack growth in
rail steel using acoustic
emission, Iron and Steel Making (available online). doi:
10.1179/1743281212Y.0000000051
6. M Papaelias, C Roberts, C Davis, 2008. A review on non-destructive
evaluation of rails: State-of-the-art
and future development, Proceedings of the IMechE: Part F — Journal of
Rail and Rapid
Transit, 222(4), 367-384 (Invited paper). doi: 10.1243/09544097JRRT209
7. F Garcia Marquez, R Lewis, A Tobias, C Roberts, 2008. Life cycle costs
for railway condition
monitoring, Transportation Research: Part E: Logistics and Transportation
Rev., 44(6), 1175-1187.
doi:10.1016/j.tre.2007.12.003
Details of the impact
The following list demonstrates the impact of the Railways Systems Group,
the primary
beneficiaries of are the railway network and train operators in the UK,
and overseas, with improvements
in services benefiting rail users.
Railway Point Condition Monitoring
The key measurable in the rail industry for impact is train delay
minutes. The cost associated with
delay varies dependent on the type of train service, but lies in the range
of £20/minute (non-critical
freight trains) to £160 (inter-city trains).
Collaboration on railway point condition monitoring has been ongoing with
Network Rail since
2004. Initial work helped to develop a business case for railway condition
monitoring [5.1] which
resulted in £40M of investment by Network Rail as part of their
Intelligent Infrastructure
programme. The group has been key to this programme, providing algorithms
for fault detection
and diagnosis that have now been implemented on 5,600 out of 27,000 point
machines. `The initial
implementation was on HW type point machines, has resulted in an
estimated reduction of
29.4% of point machine faults; leading to a substantial reduction in the
amount of delay
minutes attributed to Network Rail'. In the one year period between
2010-11 there were 646,083
minutes delay on the network due to points failure. Since the rollout of
the system in 2012 the
number of delay minutes has dropped to 579,063 [5.2].
Following the success of this work on point machine monitoring with
Network Rail, the group were
approached in 2010 to carry out a monitoring trial on the Japan Central
Shinkansen High Speed
`Bullet Train' line South of Tokyo. Following the initial data collection
exercise Japan Central
Railways seconded an employee to the University of Birmingham for 2 years
to work with the team
to develop a system for application in Japan [5.4]. Following this work,
Japan Central Railways has
begun an implementation programme on all of their Shinkansen lines. In
addition to Japan, initial
trials have been undertaken with Deutsche Bahn in Berlin [5.3] and Hefei
Metro in China.
Based on the success of the Birmingham condition monitoring algorithm
research for the Intelligent
Infrastructure programme, in February 2012 Network Rail formed a £1.65M
investment Strategic
Partnership with the group in the area of Data Integration and Management
to further develop the
existing algorithm work as well as developing new applications.
Conductor shoe monitoring
A collaborative industry research project has resulted in the University
of Birmingham together with
Southern Railway and Network Rail being awarded the Stephenson Award for
Innovation at the
National Rail Awards in 2012. The work, which developed an in-service
condition monitoring
system to assess the state-of-the-health of the power conductor rail,
automatically identifies
sections of track that put excessive force into a train's conductor shoe.
In 2012, the system
identified more than 30 locations that required remedial action in the
Southern region; previously
these locations were unidentifable. In 2012, 25,000 minutes of train delay
were caused by
conductor rail problems of this kind [5.6], with an average of delay of
405 minutes per incident. This
initial deployment of the system has therefore an estimated savings of
12,105 minutes.
Track circuit monitoring
Previous research work [3.1], funded directly by London Underground, is
now being used in this
REF period to provide expert advice through consultancy work that is
specifying and designing an
innovative track circuit condition monitoring system (hardware, algorithms
and architecture) for
London Underground. This system will revolutionise how London Underground
maintain one of
their key assets, allowing them to move from a scheduled to reactive
maintenance regime. London
Underground will invest `several million pounds over the next 5 to 10
years' in this technology [5.5].
Bearing Monitoring
In 2012 Hitachi received a £7 billion order from the Department for
Transport to build a new fleet of
trains for the UK. One of the key criteria for selection of Hitachi was
due to the proposed method
for the safe rollout and the ongoing life cycle cost benefits of the new
train. This, in part, is based
on a series of monitoring systems to ensure the health of key components.
In the area of wheel
bearing safety, these assertions have been based on expert advice from
research undertaken by
the University in collaboration with Hitachi to develop a prototype
acoustic monitoring system that
was able to detect and diagnose bearing and gearbox faults on the new
train. During Phase 1 of
the project field trials took place to verify the work. Phase 2, which is
currently underway, is
developing a full prototype system that will be sited on the High Speed 1
line in early 2014.
Inertial Measurement Unit
In 2011 and 2012 in-service inertial measurement units have been
developed and deployed on two
in-service trains for MerseyRail and Southern that are able to identify
track locations that require
maintenance. These systems are the first of their kind in the UK, and are
currently operating on the
UK network. As part of the EPSRC Track 21 Programme Grant, the system
monitoring the track in
the south of England has been used by Network Rail to help steer and
monitoring a track renewal
at Black Boy Lane Level Crossing in the Southern Region.
Gauge corner cracking instrumentation
In 2012, the University demonstrated the first high speed gauge corner
cracking test system in
collaboration with REFER, the Portuguese railway infrastructure manager.
The system is designed
to detect and quantify rolling contact fatigue cracks on the rail gauge
corner. The system
integrates ultrasonic, vision and ACFM (alternating current field
measurement) technology. The
integration of these systems allows high speed inspection to be carried
out. The system operates
at up to 120 kph, whereas conventional systems typically operated at 30-40
kph
Energy monitoring
Environmental impact is evident throughout the groups work; however it is
particularly predominant
in this study. In 2012 a monitoring and simulation study was undertaken to
drive a system-wide
energy saving on the MerseyRail network. The study has been developed for
long-term monitoring
of the MerseyRail network looking at DC railway power systems to
understand the losses, and
hence set the price of the energy paid by the train operating companies
throughout Britain. The
work is led by the University of Birmingham and is supported by Network
Rail and the Department
for Transport with in kind contributions from MerseyRail, Association of
Train Operating
Companies, the Rail Safety and Standards Board, London Underground and
Angel Trains. The
work has highlighted key energy saving strategies and will inform future
train procurement for the
MerseyRail, and other networks. The results of the study have been issued
to the Office of the Rail
Regulator in Network Rail's report TPD-NST-021 LOSS-REP-0012 which is
being used to set the
price of the energy paid by the train operating companies throughout the
UK [5.7]. This is a key
step in helping the rail industry meet its target of achieving a 20%
reduction in energy usage by
2020 (which equates to an annual saving of 580 GWh of electricity and 91
million litres of diesel).
Following the success of this work, a project is now underway with
Guangzhou Metro in China.
Winter mitigation
Since winter 2009 the group has developed specific instrumentation and a
number of national test
rig to help Network Rail manage the effect of snow and ice. The research
undertaken has helped
Network Rail in understanding the cause of winter problems, and hence
write requirements and
standards for the rail industry for winter mitigation measures and assess
the develop
benchmarking tests evaluate manufacturers solutions. So far the University
has helped specify and
evaluate over 30 different products, on which Network Rail now spends
approximately spent
around £200k to £500k per year. The work undertaken by the University was
identified as a
successful collaboration case study in the Department for Transport's
Railway Industry Research
Strategy document [5.8]. Furthermore, in 2010 the Rail Industry's National
Task Force, to which
the University provides advice, referred to the importance of the work
being undertaken by the
University when giving evidence to the Transport Select Committee [5.9].
Sources to corroborate the impact
1. To corroborate work with Network Rail on condition monitoring business
case generation (paper
co-authored with J Amoore, Research and Development Manager at Network
Rail): C Roberts, R
Lewis, J Amoore, 2006. Making the case for railway condition monitoring,
Proc. of the 7th World
Congress of Railway Research, Montreal, (http://www.uic.org/cdrom/2006/wcrr2006/pdf/652.pdf).
2. To corroborate algorithm usage as part of the Intelligent
Infrastructure programme: Evidence in
a letter from the Intelligent Infrastructure Technical Manager, Network
Rail.
3. To corroborate development of algorithms for Network Rail, Deutsche
Bahn and Japan Central
Railway. University partnerships for a better railway, Science in
Parliament, Journal of the
Parliamentary and Scientific Committee, Spring, 7-9 (by John Amoore,
Research and Development
Manager at Network Rail): (http://www.vmine.net/scienceinparliament/sip68-1.pdf).
4. To corroborate collaboration with Japanese Central Railways (paper
co-authored with Tomo
Asada, Japan Central Railways): T Asada, C Roberts, T Koseki, 2013. An
algorithm for improved
performance of railway condition monitoring equipment: alternating current
point machine case
study, Transportation Research Part C: Emerging Technologies, 30,
81-92.
5. To corroborate saving to London Underground: Evidence in a letter from
the Signals
Maintenance Sponsor, London Underground.
6. To corroborate the impact of the conductor shoe monitoring research:
Prevention is better than
cure — Southern's TRIME project, Rail Strategies, September 2011,
92-93.
7. To corroborate Network Rail engaged the University of Birmingham to
undertake train simulation
and transformer rectifier modelling: Network Rail report — Estimate of DC
losses: Electricity Supply
Tariff Area Analysis TPD-NST-021 LOSS-REP-0012:
8. To corroborate the range and importance of work undertaken on winter
mitigation (Department
for Transport Rail Industry Research Strategy): http://assets.dft.gov.uk/publications/rail-industry-research-strategy/railresearch.pdf
9. To corroborate statements relating to the importance of the work
undertaken to Network Rail's
winter programme (reference to the work of the University by the Rail
Industry's National Task
Force when giving evidence to the Transport Select Committee):
http://www.publications.parliament.uk/pa/cm201011/cmselect/cmtran/writev/weather/m13.htm