stasha jovanovic - modern railway infrastructure asset management
TRANSCRIPT
Modern Railway Infrastructure Asset Management
Stasha Jovanovic
Executive Manager - Asset Management
MER MEC S.p.A., Italy
Keywords: Railway, Infrastructure, Condition-Monitoring,
Asset-Management, Maintenance.
Abstract
The Paper discusses various Condition-monitoring techniques
and their optimal utilization for Railway Infrastructure Asset
Management Systems (RI-AMS) purposes, as well as main RI
AMS sub-systems and activities they are supposed to handle.
1 Introduction
Complexity of today’s railway sector imposes high and often
conflicting demands on Rail Infrastructure Managers. The
shear vastness of Railway Networks requires advanced tools
and methods to aid humans in managing them efficiently.
This problem necessitated in the recent years the introduction
and application of Railway Infrastructure Asset Management
Systems (RI-AMS). Knowing that the condition-based
approach was undoubtedly by far the most efficient existing
approach to maintenance engineering, modern RI-AMS are
almost entirely based on collecting, processing and utilizing
asset-condition data. This clearly made Railway Infrastructure
Condition-Monitoring the single most important building-
block of any RI-AMS, because the overall managing
capabilities of RI-AMS will greatly depend on the quality of
the available Monitoring systems and data they produce.
The purpose of monitoring is usually twofold. The first,
immediate reason is obviously the detection of the
irregularities that could endanger safety and reliability of the
railway traffic. However, in addition to this, if a monitoring
technique is continuous and fast enough to allow consecutive
monitoring runs to be performed in regular time intervals, an
extremely important temporal aspect is obtained which is of
essential importance for a successful condition-based asset
management. This means, that such monitoring techniques
can provide detailed insight into the infrastructure assets’
behavior over time, enabling condition-forecasting and
consequent maintenance & renewal (M&R) planning. This
concept effectively represents the ultimate goal of any
Condition Monitoring as well as that of the entire Railway
Infrastructure Asset Management as a whole.
2 Railway Infrastructure Condition Monitoring
& Analysis
All activities related to the asset diagnostics, condition
analysis, planning and consequent execution of maintenance
and/or renewal works can be structured in the so-called
condition-based maintenance chain. The condition-based
maintenance chain is traditionally composed by the following
main phases (illustrated in Figure 1):
• Monitoring, surveys made by either measuring vehicles
or other inspection systems that produce diagnostic data.
• Analysis, the necessary processing, data storage for
future usage and visualization of diagnostic data.
• Warning/Alerts Generation, the generation of
information like defects, quality indexes, alerts, etc. to be
used for maintenance purposes.
• Planning, the production of M&R plans to optimize.
• Optimization, the optimization of the M&R plans to
choose a final one to schedule.
• Scheduling and Execution, the final phases oriented at
the resource allocation and works execution.
• Management, the final global control of overall
performances of the maintenance process.
• KPIs
• Efficiency
• Efficacy
Monitoring Data
Analysis
Alert
generation
ExecutionScheduling
Measurements/
Ispections/
Critical Defects
•Measure of: Track, Rail, Ballast,
Overhead Line, Switches & Crossing, etc.
• Critical defects Detection
Structured Data
• Single and cross/multiple
parameter analysis
Alerts/Defects
• Quality Index Calculation
• Defects List Generation
• Issuing Alerts
• Issuing Work Orders
• Allocating
Resources
•Closing out the Work Order with technical (location, …) and
economical (labor hours) information
Building Work History
Activities
Object
Results
Maintenance and Renewal (M&R) WorksDefects
Scenarios
Planning
• Degradation Speed and Work History Analysis
• Clustering of
Works
• Production ofScenarios
Optimisation
OptimisedScenario
•Checking Line Availability and Resources
• Setting
Priorities
Control
M&R Actionsand Policy Change
Scheduled Work Order
Measuring and Video Inspection Systems
Asset ManintenaceManagement Systems
Systems
Decision Support Systems
Enterprise Resource Planning (ERP) / Enterprise AssetManagement (EAM)
&
•Validation and localization of data
• KPIs
• Efficiency
• Efficacy
Monitoring Data
Analysis
Alert
generation
ExecutionScheduling
Measurements/
Ispections/
Critical Defects
•Measure of: Track, Rail, Ballast,
Overhead Line, Switches & Crossing, etc.
• Critical defects Detection
Structured Data
• Single and cross/multiple
parameter analysis
Alerts/Defects
• Quality Index Calculation
• Defects List Generation
• Issuing Alerts
• Issuing Work Orders
• Allocating
Resources
•Closing out the Work Order with technical (location, …) and
economical (labor hours) information
Building Work History
Activities
Object
Results
Maintenance and Renewal (M&R) WorksDefects
Scenarios
Planning
• Degradation Speed and Work History Analysis
• Clustering of
Works
• Production ofScenarios
Optimisation
OptimisedScenario
•Checking Line Availability and Resources
• Setting
Priorities
Control
M&R Actionsand Policy Change
Scheduled Work Order
Measuring and Video Inspection Systems
Asset ManintenaceManagement Systems
Systems
Decision Support Systems
Enterprise Resource Planning (ERP) / Enterprise AssetManagement (EAM)
&
•Validation and localization of data
Figure 1: Condition-Based Maintenance Chain
Today, railway infrastructure/maintenance managers are
faced with the problem of implementing the condition-based
maintenance chain with a cost-effective solution taking
advantage of the latest technologies. As illustrated in Figure 2
infrastructure includes many assets such as track, overhead
line, S&C, civil-engineering structures, etc. that can be
maintained with a support of many systems, adopting several
policies such as corrective, preventive, predictive, risk-based
and others.
……
TrackTrack
Overhead LineOverhead Line
TelecommunicationsTelecommunications
SignallingSignalling
CyclicCyclic
Measuring Systems for Track, Overheard line and
Vehicle Dynamics
Measuring Systems for Track, Overheard line and Vehicle Dynamics
SoilSoil
BridgesBridges
PredictivePredictive
CorrectiveCorrective
Condition-BasedCondition-Based
Vision Systems for automatic recognition of defects
Vision Systems for automatic recognition of defects
Decision Support SystemsDecision Support Systems
Monitoring SystemsMonitoring Systems
Positioning SystemsPositioning Systems
Inspection SystemsInspection Systems
Maintenance Policies
InfrastructureTechnologies
ERPERP
GISGIS Palm ApplicationsPalm Applications
BallastBallast
RailsRailsSleepersSleepers
……
TrackTrack
Overhead LineOverhead Line
TelecommunicationsTelecommunications
SignallingSignalling
CyclicCyclic
Measuring Systems for Track, Overheard line and
Vehicle Dynamics
Measuring Systems for Track, Overheard line and Vehicle Dynamics
SoilSoil
BridgesBridges
PredictivePredictive
CorrectiveCorrective
Condition-BasedCondition-Based
Vision Systems for automatic recognition of defects
Vision Systems for automatic recognition of defects
Decision Support SystemsDecision Support Systems
Monitoring SystemsMonitoring Systems
Positioning SystemsPositioning Systems
Inspection SystemsInspection Systems
Maintenance Policies
InfrastructureTechnologies
ERPERP
GISGIS Palm ApplicationsPalm Applications
BallastBallast
RailsRailsSleepersSleepers
Figure 2: Modern Concept of Integrated Railway
Infrastructure Condition Monitoring
All these systems such as Diagnostic Systems (measuring
systems, visual inspection systems, etc.), Asset Management
Systems (AMS), Decision Support Systems (DSS) and others
(e.g. GIS) have their impact on the condition-based
maintenance chain. In particular, the Diagnostic Systems and
related data-analysis tools (e.g. AMS & DSS) are aimed at
supporting the following three phases of the condition-based
maintenance chain:
• Monitoring: Usually, during the measuring process
different types of diagnostic data are collected. Acquired
data are processed and analyzed for initial defects-
generation and classification. The main defects detected
during this phase are the so-called “critical defects” that
require immediate intervention. They are normally
transmitted in real-time (e.g. e-mail, fax, SMS, etc.) to the
responsible maintenance personnel to schedule further on-
site inspections and/or corrective works. In general, all the
acquired data are stored temporarily on the measuring
systems and then transmitted for further analysis.
• Analysis: Unlike the Monitoring Phase which sole purpose
is to acquire the data, the Analysis phase already falls
within the domain of Asset (Maintenance) Management.
After the acquisition, data are validated, accurately
localized on the railway network topology and finally
stored in the proper data warehouse for the purposes of
Asset (Maintenance) Management. Only starting from this
phase, acquired data can be correlated with all other
existing data. Data correlation is fundamental for obtaining
global understanding of how the overall infrastructure is
behaving. In fact, it is very important to monitor and keep
track of infrastructure conditions over time and also
correlate different infrastructure aspects such as track
geometry and ride quality, pantograph and overhead wire,
track geometry and overhead line geometry, etc. When all
measuring systems are installed on a single train/vehicle
(“run-once-and-get-all”), measurements are perfectly
synchronized in space and time, so data can be analyzed in
an integrated way and correlated in both space and time.
• Warning/Alert Generation: Stored data coming from the
analysis phase are used for the identification of short-time
and limited scope of primarily interventive maintenance
priorities, namely alerts, resulting from the application of
prescriptive norms (e.g. attention vs. intervention
thresholds, quality indexes, etc.) exclusively on the defect
level. The subsequent phases (e.g. planning, optimization,
etc.) supported by dedicated Asset Management / Decision
Support Systems (e.g. RAMSYS, see Chapter 4 –
“Analysis AND PLANNING software”) will manage all
these alerts and others (e.g. cyclic, renewal alerts, etc.) in
the short, middle and long-term time-frames, producing
M&R scenarios.
A wide range of diagnostic systems is available to support the
three described phases of the condition-based maintenance
chain. Table 1 includes the main categories of systems
available on the market and produced by MER MEC:
Table 1: Diagnostic Systems Category Type of measurement
Track measurement Track Geometry
Rail Profile
Rail Corrugation
Ballast Profile
Overhead line
measurement
Overhead Line Geometry
Contact Wire Wear
Pantograph Interaction
Arc Detection
Overhead Line Electric Parameters
Vehicle dynamics
measurement
Ride Quality
Body, bogie and axle boxes accelerations
Wheel-Rail Interaction Forces
Wheel-Rail Contact
Vision systems Automatic Rail Surface Defects detection
Automatic Overhead Line Defects detection
Video inspection Railway Section and Surroundings
Track Surface
Overhead Line
Platforms
Way Side
Other monitoring Signaling
Telecommunication Quality
Environmental Temperature
Tunnel Ceiling status detection
Railway infrastructure kinematic envelope/gauge
Tunnel detection system
Positioning System
Monitoring of Signaling systems
Time Radio-Synchronization system
Diagnostic systems can be assembled and integrated on
railway vehicles, allowing monitoring at low and high speeds.
Depending on the needs and the budget of the railway
operator, different types of configuration can be evaluated.
All diagnostic systems can be assembled and integrated on:
• Dedicated vehicles (e.g. those developed by MER MEC)
or supplied by the Railway Operator
• Commercial vehicles (locomotives/passenger/freight
trains)
All measuring systems are available for any type of track
gauge and they can be operated:
• With operators on-board and real-time analysis (manned)
• Without operators on-board and with automatic data
retrieval (unmanned)
2.1 Track Measurements
With the exception of drainage and substructure problems,
track deteriorates almost exclusively due to forces induced by
traffic. Forces cause destruction of all track components: rails
(fatigue & surface defects), sleepers, ballast, fastenings,
substructure, as well as cause rapid deterioration of the track
geometry (both in short & long wavelengths). In fact, tracks
with bad geometry will:
• Exhibit faster deterioration compared to good geometry
tracks that retain/keep their good shape for longer time-
spans
• Have more frequent failures of all track components,
causing accidents, traffic disruptions and speed
reductions
Therefore, track geometry influences all track components
and their service lives, so keeping good control of the track
quality brings increased revenues from the exploitation of the
line by reducing accidents, traffic disruptions and slow orders
(speed reductions) as well as M&R cost savings.
New measuring systems are available for monitoring various
track geometry parameters. They mainly adopt innovative
techniques based on no-contact opto-electronic technologies,
and no-contact measurement systems based on inertial
techniques, instead of traditional old-fashioned “contact”
track measuring systems, which adopted mechanical devices
in contact with rails.
“ROGER” system for track geometry and rail profile
measuring is fully integrated. In fact, geometrical parameters
of the track are obtained from the measurements of the real
profile of the rail. The system measures rail profiles first, then
it detects the running plane and the point of the head of the
rail placed 14mm under this plan (the “gauge point”). As
shown in the Figure 3, measurements of the profile are
obtained by means of a laser band sheet. It illuminates the
entire surface of the rail head (top and gauge sides).
Figure 3: Rail profile and track geometry measurement
devices
No parts of the system are moving (in motion), but each
component is rigidly fixed to the vehicle frame.
Measurements are realized through lasers, special sensors and
cameras. Any speed the vehicles should travel, each 50 cm
(and/or also 25 cm) a real profile of the track is taken. Then,
through software analysis, the system measures the gauge
from the rail profiles. The rail profile and the gauge point
serve as the basis for detection of the longitudinal level and
alignment of both rails adopting the “chord” technique.
An inertial system, constituted mainly by inclinometer and
rate sensors, is adopted for the measurement of cant and twist.
Twist is calculated from the measurement of the cant. All
measurements can be effectively carried out in the entire
speed range of 0 - 300 km/h, without any influence on the
accuracy. Rail wear is calculated by matching the acquired
rail profile and the nominal (as new) real profiles (obtained
from the database for the known rail types). The right and left
rail profiles (inner sides) measurements can be used to
process “equivalent conicity” (and contact gauge angle) with
a good resolution according to the number of rail profile
points.
Integrated measurement of rail profiles and track geometry as
in the “ROGER” system supports cross-correlation analysis
of the track. Track geometry and rail profile data, as well as
other data (e.g. images) can be correlated and analyzed in an
integrated manner. This allows thorough and true analysis of
the causes of certain defects (e.g. gauge defects caused by
either fastening or rail wear problems) as well as better
identification of track conditions.
2.2 Rail Corrugation
Rail corrugation is known to create significant increases in
dynamic forces, which can considerably deteriorate the long-
wave track geometry. These two things together again can
severely reduce the service lives of all track components. Rail
corrugation can cause both surface and internal defects in
rails, cracking of concrete sleepers and loosening of the
fastenings on the timber sleepers, crushing of the ballast (both
as the consequence of the higher dynamic forces, as well as
that of repeated tamping initiated by the recurring problems in
long-wave track geometry) as well as very dangerous
disturbance to the substructure.
The causal relationship between the corrugation (as the root
cause) and the dynamic forces and track geometry (as the
consequences) can best be seen from the corresponding
measurements done in Italy as represented within the
RAMSYS Asset Management System, Figure 4, which will
be described in Chapter 4. In fact on the Figure 4 several such
locations can be noticed, and having it displayed in an
obvious and user-friendly manner as in RAMSYS it does not
even take a lot of expertise to notice the causalities.
Figure 4: Corrugation consequences
However, what is perhaps most striking is if we were to take
now the location as indicated on the Figure 4 and tried to see
the progression in time of both Corrugation and its
consequences (dynamic forces and track vertical level), we
could immediately notice that they all followed identical
pattern. If we were now to include the work history view, as
seen on the Figure 5, we would see that due to the recurring
problem with the track geometry (which in fact was initiated
by the high corrugation build-up), this location was
repeatedly tamped, and yet the (track geometry) problem was
recurring. This was indeed due to the existence of
corrugation, which however was never remedied. Instead,
what this location needed was grinding and then tamping and
it would have then seen much more stable both track
geometry and corrugation. It is a pity that the information on
the surface and internal defects of rails was not available for
that location, but if it was, it would have most probably
corroborated the statement that indeed the corrugation on that
location has had multiple detrimental consequences, the worst
however of which was the one least observable – i.e. the
build-up of fatigue induced by dynamic-forces in all track
components present on that location, significantly reducing
their service lives and thus increasing the M&R costs.
Repeated Tamping
(green works)
Alignment
Level
Corrugation
Dynamic Forces
Growth of Level over
time (6 measurements)
Growth of Corrugation over time (5 measurements)
Repeated Tamping
(green works)
Alignment
Level
Corrugation
Dynamic Forces
Growth of Level over
time (6 measurements)
Growth of Corrugation over time (5 measurements)
Figure 5: Corresponding time-progression of Corrugation and
Track Geometry (Vertical Level) and repeated
(unnecessary) Tamping remedying the symptom instead
of the root-cause
Fully respecting the importance of Corrugation has prompted
MER MEC to develop a highly-accurate corrugation
measurement system (Figure 6) effectively allowing railways
to measure and monitor the existence and build-up of
corrugation, and with the help of powerful tools like
RAMSYS, to correlate it with other data in order to extract
the intrinsic and salient mutual interrelationships and identify
the true root causes of the problems and devise the most
adequate remedial activities.
Figure 6: Rail Corrugation Measuring System
2.3 Vehicle Dynamics
In order to study the interaction forces which act at the wheel-
rail contact point and the oscillatory motions to which the
vehicle is subjected during the running, different parameters
have been introduced to quantify the vehicle safety against
derailment, its aggressiveness towards the track and the
passengers’ comfort. Moreover, some types of defects of the
track can also be detected from this kind of analysis. Three
main classes of systems are available for the measurement of:
• Wheel-Rail Interaction Forces
• Bogies and coach real-time accelerations
• Wheel-Rail Contact Geometry
The UIC & European Norms (CEN) require direct
measurement of the lateral force Y and the vertical force Q,
acted by the wheel on the track, in order to demonstrate safe
running conditions (UIC 518). For this purpose, the following
monitoring aspects are required
• Real time Y & Q forces
• Real time Y/Q ratio
• Lateral acceleration correlation.
Furthermore, the following analyses are also available:
• Of the Wheel profile with optical technology
• Of the Wheel-rail coupling, delta-r (∆r) calculation,
angles of contact and equivalent conicity at several
values of sigma.
Vehicle dynamics measurement are carried out using systems
based on Strain Gauges instrumentation on wheels making
use of telemetry system for signal extraction, non-contact
Laser displacement and accelerometer sensors. In particular,
accelerometer sensors detect the mechanical vibrations of
railway vehicles. These vibrations depend on the vehicle
characteristics (e.g. quality of primary and secondary
suspensions, etc.) as well as the quality of the rolling plane
(e.g. longitudinal level, alignment, twist, rail joints defects;
irregular wear of the rail-wheel contact profile, etc.).
3 Automatic Infrastructure Inspection
Railway operators looking for improving safety of their
networks must regularly inspect the infrastructure to avoid
accidents as well as introduce most cost-efficient ways of
carrying out such inspections. Data collected during
inspections play an important role for both safety and
condition monitoring. For example, the swelling or
subsidence of the ballast beds or the presence of objects
infringing clearance profile are hazardous for rail vehicles.
Rail defects, like black spots, can propagate inwards into the
rail-head, and when they reach a dangerous depth, they may
propagate downward transversely, producing fractures of the
rail, so it is important to keep infrastructure under inspection
in order to timely identify the anomalies.
Inspections can be done on foot (by walking) or by vehicle,
adopting traditional video inspection systems for image
acquisition and video capturing, or innovative vision systems
for automatic defect detection. Compared to on foot
inspection, automatic inspections consume less resources (e.g.
time, line interruption, etc.) and moreover they do not require
safety measures for allowing people to access the network
lines.
In general, video and vision systems mounted on-board
trains/vehicles provide the possibility of checking different
aspects of the entire environment surrounding the
infrastructure as well as the infrastructure itself. Moreover, if
these systems are integrated with other diagnostic systems,
they allow:
• Linking specific infrastructure defects to possible
environmental conditions that might have caused the
defects.
• Evaluating how infrastructure environment evolves and if
any change can produce eventual problems to the normal
railways activities.
• Analysis of the images in specific points of the railway
network for safety and control purposes.
3.1 Track Surface Inspection Systems With Automatic
Defects Detection
MER MEC’s approach to Track Surface Inspection using
“Vision Technologies” is based on the framework composed
by 3 subsystems:
• TSIS: Track Surface Inspection Subsystem
• Joint Gap and Head Checks Inspection Subsystem
• TSMS: Track Surface Measurement Subsystem
“Track Surface Inspection System” provides innovative
functions for real-time video monitoring of track condition
and automatic recognition of resulting defects. Traditional
video inspection of the rail surface imposes that specialized
personnel analyze visually all the recorded images. This
activity is clearly time consuming and potentially hazardous
because the results are strictly dependent on the ability of the
viewer to detect possible anomalies and report critical
situations. As opposed to that, Vision Systems for defect
detection automate the defect recognition and speed up the
inspection process by reducing the image analysis time as
well as increase the reliability of the detection process.
The “Track Surface Inspection System” can be used for:
• Detection of Sleepers types & moving sleepers
• Rail fastenings types detection and condition, as well as
fastenings in (unwanted) contact with wheel flanges
• Rail surface defects
o Black Holes
o Burnings
o Rail Break
o Crushed Head
o Cracks (thickness > 0.7 mm)
• Base plate condition in absence of ballast and pincers
position
• Joint Gap measurement estimations & Head Checks
Inspection
• Checks of ballast irregularities, vegetation, structural
condition of magnets, pass-throughs, axle counters, AFI
and ETCS balises
o Detailed analysis
o Markings Detection
o Missing Bolts
o Released Shoulder Plate
o Misfit rail pads
o Distance/position of Clammers to the
sleepers/fastenings
Images
Analyses Historical Section
Analyses Infos
Kilometric reference
Message Area
Images[HEAD CHECK]
Status
Status
Images
Analyses Historical Section
Analyses Infos
Kilometric reference
Message Area
Images[HEAD CHECK]
Status
Status
Figure 7: Track Surface Inspection System Analysis
The “Track Surface Defect Detection System” is based on the
no-contact optical technology using high-speed line-scan
cameras for track images acquisition. Enhanced vision
algorithms identify and classify defects according to their
properties and/or their position in the track. A special
illumination system allows the system to operate properly at
every light condition. Synchronization with the vehicle’s
encoders allows identification of its position on the track and
its kilometric point. The analysis can be done image by
image. In real-time, the system extracts rail images, and
identifies their position using odometer. The on-board system
allows acquisition, processing, displaying and storage of the
image-frames of both rails. The post-processing analyzes each
image to locate automatically the defects according to their
size, position, etc.
Figure 8: Track Surface Inspection System – Rail Surface
Analysis & Defect Detection
“Joint Gap and Head Checks Inspection Subsystem” is
composed by two high speed cameras, completely integrated
with the standard system, which allow automatic detection
and highly accurate measurement of rail joint/weld gaps and
rail head-checks (their length, width, angle and clustering),
and all that at very high speeds reaching 250 km/h.
Size/width of rail joints and welds is very important cause it
directly influences the rise of dynamic forces, which again
decisively influence the life of all track components beneath
and in the vicinity.
Figure 9: Joint Gap and Head Checks Inspection Subsystem –
Joint/Weld detection & measurement
Rail head-checking (rolling contact fatigue – RCF, or gauge
corner cracking - GCC defects) in turn has become an issue of
an outmost importance for railways World-wide in the recent
years due to their sudden and often worryingly drastic rise
observed in the recent years. RCF defects like head-checks, if
left unattended could develop very quickly and turn into rail
breaks of often fatal consequences, as could have been seen
from the tragic accident at Hatfield, UK, where four people
were killed and a further seventy injured. When a preliminary
investigation found that a rail had fragmented while the train
had passed over it, and that the likely cause was GCC, it led
to temporary speed restrictions being imposed on huge
lengths of Britain's railways, effectively crippling many
routes, while checks were carried out on the rails.
Being able to monitor this obviously critical
phenomenon/defect, and especially in such an accurate,
reliable and above all efficient manner like with the above
system with automatic detection capabilities, railways can
make proper assessments of the situation and its gravity as
well as decide on adequate actions to be taken (typically
grinding, if not too late or re-railing) in a timely manner, thus
drastically improving the safety of the railway traffic.
“Track Surface Measurement Subsystem” adopts area scan
cameras in association with a set of laser blades to accurately
measure the position of various track objects, with the aim of
executing the following verifications that require high
intensity processing:
• Detection of ballast irregularities
• Vegetation check
• Distance measurement between different rail fastening
components
• Checking of the structural condition of magnets, pass-
through, axle counters, AFI, ETCS balises
Figure 10: Track Surface Measurement Subsystem
4 Analysis & Planning
The planning phase can be realized by building the
appropriate historical knowledge-base supported by further
software tools for easy data access/correlation (e.g. work
history data), processing and decision-making. In order to
fully support/cover the planning phase, MER MEC has
designed and developed a special software platform for the
overall integrated Asset Management including M&R
planning, named RAMSYS (Railway Asset Management
SYStem). RAMSYS represents a dedicated system for
Railway Infrastructure Maintenance Management designed to
help Railway Infrastructure Managers to handle complex
multidisciplinary and multidimensional process of
infrastructure degradation by integrating all necessary
information through advanced visualization (Figure 11) and
analytical capabilities necessary for optimal planning of
M&R works. RAMSYS system, being extremely complex,
requires lot of space for proper description, hence in this
paper only the basics will be provided. The main idea
however is that it puts full focus on utilizing condition data
for work planning. All condition data coming from various
Diagnostic Systems are utilized simultaneously, together with
the complete history to capture/define the "behavior" of each
and every asset and then to use this "historic-perspective" to
generate the "forecasted behavior", with the use of
sophisticated deterioration models. Only based on the
forecasted behavior and comparison to the required quality
and incurred costs, the optimal combination of activities
(M&R works, as well as inspections) can be defined and
proposed for execution. Thus, RAMSYS has the ability to
balance Maintenance versus Renewal works, as well as
quality versus costs, in order to define the optimal scenario,
i.e. the M&R policy/strategy.
a) Integrating various data in the same View
Work HistoryWork History
Dynamic Forces Measurements
Dynamic Forces
Measurements
Track Quality
Measurements
Track QualityMeasurements
Track
Segments
Track
Segments
Asset
Inventory
Asset
Inventory
System
Management
System
Management
Corrugation
Measurements
Corrugation
Measurements
Change of Corrugation
over time for the
selected stretch
Change of Corrugation
over time for the
selected stretch
b) Condition-measurements vs. Infra. Assets inventory
System
Managem ent
System Managem ent
W ork HistoryWork HistoryDynam ic Forces Measurements
Dynamic Forces Measurem ents
Track layoutTrack layout
Rail W ear
Measurements
Rail Wear
Measurements
Corrugation
Measurements
Corrugation
Measurements
Asset InventoryAsset Inventory
Track Quality
Measurements
Track QualityMeasurem ents
Video Inspection
Im ages
Video Inspection
Images
OHL Height, Stagger
& Wear
OHL Height, Stagger & W ear
OHL Height, Stagger
& Wear
OHL Height, Stagger & W ear
OHL Height, Stagger
& Wear
OHL Height, Stagger & W ear
OHL Height, Stagger
& Wear
OHL Height, Stagger & W ear
OHL Height, Stagger
& Wear
OHL Height, Stagger & W ear
OHL Height, Stagger
& Wear
OHL Height, Stagger & W ear
OHL
Inventory
OHL
Inventory
c) Layout vs. Raw Track Geometry Measurem. vs. Work
History & Infrast. Assets Inventory & Photographs/movies
Work HistoryWork HistoryWork HistoryWork HistoryWork HistoryWork HistoryWork HistoryWork History
User-definable Threshold
User-definable Threshold
Degradation Trend
Degradation Trend
Work HistoryWork HistoryMeasured Values
Measured ValuesWork HistoryWork HistoryMeasured Values
Measured Values Planned WorkPlanned Work
System Management
System Management
List of Parameters shown in the View and their
characteristics
List of Parameters shown in the View and their
characteristics
d) Integrated Deterioration Modeling and Forecasting view
Figure 11: Examples of RAMSYS Advanced Visualization
5 Conclusion
The described diagnostic systems and consequently the use of
the acquired data, play fundamental role for any railway
infrastructure owner/manager and/or operator mainly for two
reasons.
• First, infrastructure in poor condition and with poor
performance compromises the railway network
operations and safety and can cause high-cost
consequences such as corrective maintenance, traffic
interruptions and speed reductions.
• Second, M&R management represents the largest part of
railways’ expenditures as well as requires significant
resources (i.e. people, material, machines and/or line
interruptions / possessions), so even the smallest
planning errors can cause tremendous detrimental
consequences. On the other hand, even the marginal
improvements in the control and management of the
infrastructure could yield significant absolute savings.
MER MEC systems described in this paper are aimed at
developing a comprehensive solution including proper set of
measuring, inspection and analysis tools for supporting not
only the diagnostics of the railway infrastructure but also the
planning of M&R works and improving the assertive power
in taking M&R decisions. The full solution can be configured
according to the railway owner/operator/maintainer’s needs
taking into account budget as well as other aspects of railway
infrastructure to monitor and maintenance processes in place.
Main benefits of the described systems include:
• Reliable and fast data collection
• Measurements are in the digital format and as such they
can directly be used to build a historical knowledge base
to be used for advanced analysis
• Earlier/timely identification and correction of critical
defects and mitigation of risks of critical defect
occurrence
• Efficient usage of track access times, thus increasing
track availability for the revenue traffic as well as freeing
the scarce time for other important engineering works
• Measurements and data related to different aspects of the
infrastructure can be integrated and correlated
• Transition from corrective to on-condition and
predictive-preventive maintenance
• Choosing optimized M&R plans based on true
infrastructure conditions
The ultimate goal however is of course to increase the
infrastructure safety and availability at minimum of (M&R)
costs, which definitely justifies and pays off all the
investments and efforts necessary for deployment of a full
solution for implementing in an effective manner the full-
scale condition-based maintenance chain.
6 References
[1] G. Aurisicchio, et al, “Infrastructure Monitoring
Systems for Improved Operation and Safety in CVRD”,
8th International Heavy Haul Conference, Rio de
Janeiro, Brazil, (2005)
[2] G. Aurisicchio, et al, “A fuzzy logic based filter for
spike-noise detection in railways monitoring systems”,
IEEE International Workshop on Soft Computing in
Industrial Applications, Binghamton University,
Binghamton, New York, (2003)
[3] S. Jovanovic, “Track Quality Analysis and Consequent
Decision Making”, 8th International Heavy Haul
Conference, Rio de Janeiro, Brazil, (2005)
[4] S. Jovanovic, “Railway Track Quality Assessment and
related Decision Making”, The American Railway
Engineering and Maintenance of Way Association
(AREMA) 2006 Annual Conference, Louisville, USA
(2006)