NDT Techniques in Railway Structure Analysis
M. Silvast 1, M. Levomäki2, A. Nurmikolu3, J. Noukka4
1
2
Roadscanners Oy, Tampere, Finland, Finnish Rail Administration, Helsinki, Finland,
4
Tampere University of Technology, Tampere, Finland, Ramboll Finland Oy, Tampere, Finland
3
Abstract
In 2004 Roadscanners Oy, Ramboll Finland Oy and the Tampere University of Technology started, in
cooperation with the Finnish Rail Administration, a research project to improve the Ground Penetrating
Radar (GPR) techniques used to survey railways and the quality of the structures and subgrade soils
beneath.
The main goal of this project was to develop GPR data collection and analysis techniques to provide
more precise information about the thickness and material properties of railway structures and subgrade
soils with a special interest in analyzing the ballast quality and frost susceptibility of subgrade soils. The
project has included the design and testing of different GPR equipment and antenna configurations, test
surveys on known and artificially created problem sections in the Finnish railway network. The project has
also entailed the development of new algorithms to calculate material parameters and Railway Doctor
software which is used to perform an integrated analysis of the GPR data together with other data
collected from the railway, such as drilling and laboratory analysis data.
This paper will present a summary of results that demonstrate the great potential that the GPR technique
has in surveying railway structures as long as the data is collected using high quality GPR systems and
the proper antenna configurations. The paper also examines the need for special algorithms for
processing GPR data especially to detect if the ballast has too much fines and is spent. Results of the
tests with the new 3D GPR system, which provides three-dimensional information from the railway
structure, will also be discussed.
The paper will also present some case histories where this new technique has already been used on the
Finnish railway network.
1 Introduction
In Finland, the railway is an important transportation system. A large quantity of goods, materials and
people are transported by rail. In wintertime, differential frost heave can cause structural defects, which
results in vertical deviations in track geometry. Deviations can also be caused by permanent deformations
in the ballast bed, substructure or subgrade soils (Nurmikolu, 2005). These problems reduce traffic
speeds and cause economic losses.
According to the Finnish Rail Administration (2004) at the end of 2004 about 1/5 of the rail network had a
superstructure which is more than 30 years old and in need of rehabilitation. At the same time increased
costs brought on by the increase in prices of technology and materials have to be kept under control. This
arises a need for an effective non-destructive track subsurface inspection method for rehabilitation
planning.
In railway investigations, ground penetrating radar based track inspections can be used to determine a
railway’s structural thickness and to evaluate the reason for different kinds of defects and their sources
with a minimal amount of drilling. During recent years, GPR technology has been improving: new systems
use faster processors and allow the use of higher frequency antennas. The processing and interpretation
software have also improved. Past experience has demonstrated GPR to be a very useful non-destructive
testing method for railways with several major advantages (Hugenschmidt, 1998, 2000; Gallagher et al.,
1998; Olhoeft and Selig 2002; Sussman et al. 2002, Smekal et al. 2003; Saarenketo et al. 2003).
Foremost among these advantages are fast measurement speed and results that provide a continuous
subsurface profile of the survey target with differentiated structural layers.
On assignment of the Finnish Rail Administration a research project on GPR based railway surveys has
been carrying out by Roadscanners Oy, Ramboll Finland Oy and Tampere University of Technology. The
project included GPR measurements on several test sections in Finland. The goal of the research project
was to test the suitability of GPR for surveying railway structure thickness, evaluating ballast quality and
locating frost susceptible areas. The new 3D GPR system was tested for modeling concrete pile
structures under track. The research group completed these test surveys during 2004-2005.
2 GPR Technique in Railway Investigations
2.1 GPR Method
Ground penetrating radar (GPR) is a non-destructive testing (NDT) method that uses a radio wave source
to transmit a pulse of electromagnetic energy into the object. The reflected energy, originating within the
object at interfaces between materials of different dielectric properties is received and recorded for
analysis. GPR data consists of changes in reflection amplitude, changes in the arrival time of specific
reflections and signal attenuation. The measured GPR data is presented as a continuous profile (figure 1)
which presents the reflections from layer interfaces along the measurement line.
Figure 1. Example of 400Mhz antenna GPR profile on the left and a single scan on the right side.
When applied to the analysis of railways, GPR can be used to detect railway structures, determine layer
thickness and subgrade soil types. This information can further be used to analyze the mixing of materials
or pumping and analyze the cause of structural defects. The GPR data helps to determine track
subsurface conditions such as layer thickness and locating insulation boards. (Saarenketo et al., 2004).
2.2 Data Collection
The GPR data was collected using a VR Ltd, Finnish Railways maintenance vehicle (Tka 8) on which a
two-channel SIR-20 GPR system, manufactured by GSSI (Geophysical Survey Systems Inc.), was
mounted with different antenna configurations. All of the data was interpreted and analyzed using Railway
DoctorTM software. The data collection rate was controlled by an optical encoder (DMI) attached to the
wheel of a truck pulled by the engine. During the survey, RDS-GPS coordinates and digital video were
recorded with RD Camlink software.
For different antenna configurations a special antenna rack system was developed. This enabled the
testing of different antenna configurations for gaining the best measurement results. The two-channel
system enables simultaneous use of two GPR antennas. The antennas were suspended 30 cm above the
ground to avoid damaging them. This also increased the measurement speed to 40 km/h. The antennas
were installed at the track centreline and the antennas were orientated transversal to the travel direction
(figure 2). This was done because the antenna radiation pattern is narrower in this direction and it
prevents interference in the data, in the form of hyperbolas, caused by the railway ties.
Figure 2. The railway truck with two GPR antennas attached in front.
2.3 Data Processing and Visualization
The data processing, interpretation and analysis were done using Railway Doctor v2.0 software. Railway
Doctor is designed especially for non-destructive railway surveys, analysis and rehabilitation planning.
The software enables the user to simultaneously view, interpret and analyze multiple datasets that use
the same co-ordinates, e.g. GPR data from different antennas, maps, digital video and track geometry
measurements, this combination of data allows the user to conduct an integrated analysis of all the
available datasets on a single screen.
3 RESULTS
3.1 Railway Ballast Evaluation
Ballast is made of crushed hard rock, of which the small-sized particles have been sieved away. The
ballast of a railway line must perform many different functions some of which are (Clark et al. 2001):
reduce stresses applied to weaker interfaces, resist vertical, lateral and longitudinal forces applied to
sleepers to maintain track position; and to provide drainage for water from the track structure. Under
constant dynamic loads, ballast material disintegrates producing fine materials. These fine materials flow
to the bottom of the ballast bed where their presence transforms the ballast to a frost susceptible material.
Accumulated organic material in the ballast bed also has a very big impact on the water adsorption
properties the material. Fine material reduces the functioning of the ballast layer and can cause geometry
problems especially in the wintertime (Nurmikolu, A., 2005).
GPR surveys of the ballast bed are generally focused on two attributes, determining its thickness and
evaluating its quality with the quality aspect especially geared towards locating sections of clean and
spent ballast. The mixing of the subgrade soil materials with the ballast can also be detected with GPR
(Hugenschmidt 2000, Brightwell and Thomas 2003). In determining the ballast thickness it is important to
know the dielectric value of the material. Since the surface reflection technique cannot be used the
options for determining the dielectric value are the WARR (Wide Array Reflection Refraction) or CMP
(Common mid-point) method. In Finland, if the goal is only to determine ballast thickness, then the
potential error caused by changes in dielectric values are eliminated by measuring the ballast thickness
when it is frozen (Saarenketo et al. 2003).
In ballast quality surveys the new approach is frequency analysis. According to Clark (2004), the clean
and spent ballast can be distinguished using Fourier analysis. Saarenketo (1998) presents that the high
content of fines and increased amount of adsorbed water causes dielectric dispersion. In order to obtain
material information the time-domain GPR data (figure 3a) must be converted to frequency-domain data
(figure 3b) using Fourier Transform.
a)
b)
Figure 3 a) Time-domain GPR signal (400MHz antenna) and b) Normalized Fourier-transformed signal in
frequency-domain as a frequency spectrum.
In order to study the effect of fine materials on the GPR signal, spent ballast was artificially produced at
the Tampere railway maintenance yard. One hundred kilograms of fine-grained (grain-size 0/3mm)
crushed rock was added to a 5 meter section over a new ballast layer. Figure 4 illustrates the Fourier
spectrum of the GPR trace over clean (continuous) and artificially produced spent (dotted) ballast. The
spectrum is calculated from the 35cm zone above the ballast bottom. It can be seen from the figure that
the area of the frequency spectrum from the clean ballast is larger than the area of the spent ballast
frequency spectrum.
Normalized Response Amplitude
1
0.8
0.6
Clean ballast
Spent ballast
0.4
0.2
0
0
400
800
1200
1600
2000
Frequency [MHz]
Figure 4. Fourier transformed frequency spectrum of the 400MHz antenna over clean (continuous line)
and spent (dotted line) ballast calculated from the 20-55 cm depth in the ballast layer.
The ballast bed thickness varies along the track line. Due to the location of the fine material in the bottom
of the ballast bed the procedure for analysis is 1) interpretation of ballast bed thickness from the GPR
data and 2) using the Fourier algorithm in order to calculate the frequency spectrum parameters at the
bottom of the ballast bed. For Fourier calculations Roadscanners has developed an algorithm, which
calculates the area of the frequency spectrum of a GPR signal at a certain depth level of the ballast bed
as a continuous measurement. The frequency sum value will be obtained, which can be used to classify
the ballast quality. When the frequency spectrum area for e.g. 1-m running average values are calculated,
changes in values can be seen. Figure 5 shows the frequency spectrum area along the test section as a
continuous curve. The low values indicate increased fine material content in ballast.
TAMPERE TESTSITE
70
FREQ. SUM
60
50
40
30
20
10
added fine material
0
0
10
20
30
40
50
60
70
80
90
100
DISTANCE [m]
Figure 5. Frequency sum along the test site with added fine materials. Small values indicates increased
fine material content in the ballast bed.
Similar results were also obtained in larger scale measurements. Figure 6 shows the profile from one test
section in Western Finland. The ballast sampling was performed after the GPR survey and the
degradation number was defined by laboratory sieving as a sum of passing percentages of 1mm, 8mm
and 25 mm sieves.
Figure 6. A data view showing interpreted ballast layer with drilling data, degradation number (higher
value=more fine materials) and frequency sum calculated from the 20 cm zone from the bottom of the
ballast. The lowest values are found from the sections with high degradation number.
Figure 7 shows the correlation between the frequency sum and degradation number from ballast
sampling in the test section measured in Northern Finland. The correlation of the two ballast inspection
methods is relatively good. The GPR measurement was made in the middle of the track and the samples
for degradation analysis were taken from the end of the tie.
Figure 7. The relationship between frequency sum and degradation number.
3.2 Thickness and Quality of the Railway Structure
Frost action causes unevenness in the tracks and as such reduces the speed of train traffic. The worst
time is late winter, between April and May. Differential frost heave occurs in places with thin structural
layers in frost susceptible subgrade soil areas. Increase of the thickness of structural layers or installation
of a new frost insulation should solve the problem. Another problematic issue is the low stability of
structures in the soft silty and peat subgrade areas.
The GPR is an effective tool in railway structure mapping. It provides continuous information about the
structure thickness along the railway line. GPR data is interpreted and drilling information is used as a
reference data. The structure layer thickness and quality can be seen from the GPR data with additional
information about insulation boards and subgrade quality. Special structures such as transition zones can
also be identified from the measurement data. When digital video is used in the interpretation, other
special features such as crossings and bridges in the GPR data are easy to locate and verify.
The GPR data clearly shows the subsurface conditions. In the project the GPR data compared very well
with the sampling data. The interpretations clearly showed the different subsurface structural layers. It
was also possible to classify the subgrade soil type using the GPR data.
Figures 8 and 9 shows the data views of the integrated GPR analysis of railway structures from two test
sections in Central Finland. The ballast and filter course are clearly visible in both figures with the
400MHz antenna data and the structural layers in the GPR data correlate well with the sampling results.
In the figure 8 the 1200 MHz antenna data shows the location of insulation boards between km 252+400
–252+506 and km 252+645-252+702. Additionally in the figure 9 the frequency sum results shows that
the high frequencies are attenuated from the GPR signal due to a peat layer with high content of water
between km 501+640 - 502+160.
Figure 8. A data view from Railway Doctor, showing a 400MHz GPR profile, an interpretation, a 1200MHz
GPR profile, drilling data and the track database showing the locations of man-made objects. The video
window and map show the location of the current view. The insulation boards are installed in the sections
with the transition zones.
Figure 9. A data view from Railway Doctor software, showing a 400MHz GPR profile, an interpretation
with ground truth data. The lowest window shows the frequency sum calculated from subgrade soil
reflection. The frequency sum has been calculated from a narrower frequency band than in figure 6.
3.3 3-Dimensional GPR Test
Recent developments in 3-dimensional (3D) GPR instruments have opened the possibility of using them
in railway structure mapping and imaging. While traditional GPR systems measure a maximum of 4
channels at once, 3D GPR permits the measurement of 31 channels on a survey line. 3D GPR also
allows measurements in both longitudinal and cross-sectional direction at the same time. The results can
be viewed as longitudinal or cross-sectional profiles or amplitude time slices.
The 3D GPR data collected for this project was a track section on peat area. The section had been
reinforced with the concrete pile slab under the track. The concrete slab had settled several centimetres
on one side. The aim of the study was to determine the level of and possible damage to the concrete
TM
slab. The 3D GPR data was collected with step-frequency Geoscope GPR system from 3d-Radar AS.
The system consists of a mainframe and 27-element bowtie antenna array (figure 10). The antenna
system was 2.6 meters long and the side distance between antenna pairs was 9 cm. The step-frequency
system was programmed to output frequencies in the frequency range 100 -2000 MHz with 2 MHz
frequency step with each antenna. The measurement density was 9 cm in both directions. The
measurement speed was about 10 km/h.
Figure 10. The 3D GPR system measuring railway structures in Ermanninsuo.
The GPR signal reflects from the railway structures and from the surface of the concrete pile slab. Using
the results, a 3-dimensional model of the railway structures and concrete slab can be calculated. Figure
11 illustrates the 3D model of the surface of the pile slab. When studying the 3D model, possibly
damaged sections of the slab can be seen in the results.
Figure 11. A 3D model of the pile slab sections from the test section. Potential damage in the pile slab
can be seen as anomalies in the model.
3-dimensional GPR mapping also provides cross-sectional information of the measurement section
structures. Figure 12 shows the longitudinal and cross-sectional profiles from ballast bed in the 3D GPR
test section in Ermanninsuo. The data gives information about possible anomalies of the ballast bed in a
transverse direction such as settlements and tamped sections. Deeper structures can also be analysed in
transverse direction.
Figure 12. Longitudinal and cross-sectional profile from Ermanninsuo. The left side window shows the
longitudinal profile with interpreted interfaces as dotted lines. The right side profile is a cross-section of
the structure with the same interfaces interpreted. The vertical black line shows the location of the cross
section profile. The cross section is a combined profile of all 26 channels of data.
4 Conclusions
The results from these research projects demonstrated GPR to be an effective non-destructive inspection
method for railway structures and subgrade soil. The method gives continuous information concerning
railway structure layer thickness, special structures and material properties. The measurement devices
have improved in recent years with faster and more accurate surveying systems becoming available. The
processing and interpretation software has also developed allowing for better visualization of processed
data. The advantages of data integration provide valuable information and insights regarding the causes
of damage in the structures.
The new development of frequency analysis of the GPR signal produces better information concerning
the material parameters of the structural layers such as ballast fouling and pumping. Subgrade soil types
can also be qualified by analyzing the frequency parameters. The new frequency calculation algorithm
enables calculation of frequency parameters in variable layer zones. These new parameters still need
further research in order to make better correlations with the current inspection system.
The 3-dimensional GPR mapping and imaging is also an efficient tool for railway structures inspection.
The system enables simultaneously measurements of longitudinal and cross-sectional profiles which can
provide valuable information concerning, for example, ballast structure. There are many potential
applications with this new system such as investigation of pile slabs, finding ballast pumping sections and
inspecting bridge structures.
The benefits of GPR methods in railway inspections are indisputable: it is a non-destructive, fast, reliable
and cost effective method. The integrated analysis of railway data helps to define the root cause of the
defects and it makes rehabilitation planning more accurate and thus more economical.
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