PROCEEDINGS of the23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Rail roughness surveys – a tool for effective environmental noisecontrol
Lisette MORTENSEN1; Stig JUNGE2
1
2

Banedanmark, Denmark

Sweco Danmark A/S, Denmark

ABSTRACTA mobile method developed by Sweco to estimate levels of rail roughness on a large scale is presented. Themethod is suitable for countrywide surveys and the data has proved to be very useful in the planning of track
maintenance both in terms of environmental noise and rail quality. Roughness measurements were carriedout twice on the Danish railway network in a two-year period, and all roughness data from these campaigns
was been stored in Banedanmark’s track measurement database. Banedanmark has developed a tool to rank
track sections according to rail quality and population density in residential areas to most effectively reduce
the amount of environmental noise from the track and to document the effect of noise reduction measures.
The measurement method uses measurement of noise from the contact point between wheel and rail to derive
an estimate of the rail roughness level and is based on the transfer function from rail roughness to acousticalnoise. The method has been tested at measurement train speeds from 60 - 120 km/h and shows a high degreeof reproducibility. Banedanmark has given these measurements a significant role in planning the large-scale
maintenance operations of grinding and milling.
Keywords: Rail roughness, Environmental noise strategy

1. INTRODUCTION
Rail and wheel roughness is the main cause of rolling noise from passing trains. Infrastructureowners therefore have an interest in regular monitoring of the rail roughness. Methods for direct
measurement of the rail roughness have been standardized (1,2) but they require direct contact withthe rail head surface and only allow for measurement of very short rail sections. They are therefore
not useful for overall surveys of the rail roughness on a complete railway network.
Indirect, i.e., contactless, measurement of rail roughness allows for measurement of longer track
sections and has to some extent been performed on railway networks through the last years. Sweco
has developed a method for contactless measurement using surface microphones mounted on a platefixture. Two country-wide measurement campaigns have been done, one in May 2017 and the otherin September 2018.
The results from these measurement campaigns are made available to staff responsible for handlingnoise complaints and the data is used to check if there are excessive roughness levels in the rail or
local defects that may cause excessive noise – thus facilitating a clear and qualified response to thecomplainants.
Also, a tool for prioritization of noise reducing measures like grinding or milling has beendeveloped which is based on the roughness measurements and which combine these measurementswith information on population density along the railway.

2. METHOD OF MEASUREMENT
The contactless method uses surface microphones to measure the noise from the wheel/rail contact
point. Using the transfer function from rail roughness to noise while taking the travelling speed into
account an estimate of the rail roughness can be found.

1
2

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limo@bane.dk
stig.junge@sweco.dk

Basically, the transfer function from roughness to noise, LH,r (f), is subtracted from the noise
spectrum, L p (f) and then transferred from the frequency domain to the wavelength domain using therelation between roughness wavelength, noise frequency and train speed (2)=−=,,(1)(2)

Figure 1 shows the microphone fixture fitted with two G.R.A.S. surface microphones with turbulence grid.

Figure 1 – microphone fixture mounted with two surface microphones
Until now, two country-wide surveys have been carried out. The first was in May 2017 using a
pocket car type Sggmrss with disc brakes. Due to problems with car rental the second campaign in
September 2018 used an old car based on the Bpmz wagon type.
Before measurement, the cars had to be calibrated, i.e., the transfer function from rail roughness
had to be found per 3rd-octave. The transfer functions were measured on both rails in three crosssections of the track and at three speeds covering the range from 60 to 120 km/h. The transfer functions
were derived from simultaneous measurement of noise on the test wagon and of combined roughness
from the wheel and track in the cross sections. All transfer functions were averaged resulting in thetransfer function used in the subsequent roughness survey measurements. Figure 2 shows the averagetransfer function.
Output from the method is the average contact point filtered rail surface roughness level on theline that the measurement car’s wheels follows on the rail. The noise from all irregularities in thetrack that are not rail roughness (switches, isolated joints, local defects etc.) are also interpreted asrail roughness and should rather be called equivalent rail roughness. On track sections where thetransfer function is unknown (in tunnels, along platforms, on bridges) the measured roughness will
not be correct but can in many cases point to some important track features that needs furtherinvestigation.

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Figure 2 – Average transfer function for car type Bpmz
Data sets are output per 1 meter track with each data set consisting of an average 3rd-octaveroughness spectrum and a single value indicator, L λCA,v (3) that relates to the environmental noise
impact.
The reproducibility of the method is quite good. Figure 3 shows measured levels of L λCA,v at threedifferent speeds, 60, 90 and 120 km/h. The originally measured noise levels prior to conversion to railroughness is shown in Figure 4.

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LλCA [dB]2015105083

83,283,483,683,884

84,284,484,6

Mileage
60 km/h

90 km/h120 km/h

Figure 3 – LλCA,120 measured at three different speeds

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84,885

130

125

120

LAEQ [dB]

115

110

105

100

95

9083

83,283,483,683,884

84,284,484,684,885

Mileage
120 km/h

60 km/h

90 km/hFigure 4 – Original noise levels, LAEQ measured at three different speeds
Subsequent measurements have shown that the method yields valid data down to a travelling speedof 40 km/h thus making it possible to measure at stations where the population density typically ishigh.

3. NOISE COMPLAINTS HANDLING
Banedanmark regularly receives noise complaints from people living close to the railway. Until
recently the staff responsible for handling these complaints had no detailed information about thetrack condition in terms of noise.
The roughness measurements have changed this since all roughness measurements have been madeavailable to the staff responsible for answering the complainants. They now have a tool for assessing
the track condition in general, and specifically if there are any track elements that cause excessive
noise, and this enables them to give much more precise and qualified answers to complainants. An
example of data presentation in GIS is shown in Figure 5. The roughness levels are colour coded withhigh levels shown in red or even pink. In this case high levels are seen at the switch in the upper partof the figure, at isolated joints in the middle and at the level crossing in the lower part.

Figure 5 – Presentation of roughness levels in GIS

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4. PRIORITAZION TOOL FOR ENVIRONMENTAL NOISE REDUCTION
Banedanmark has developed a GIS-based tool for prioritization and documentation of noise
reducing measures along the railway lines based on rail roughness data. This tool helps Banedanmark
to prioritize noise reducing activities like grinding and milling from a more socio-economic point ofview and to document the environmental effect. General maintenance of tracks will naturally yield areduction in noise levels along the railway, but the funds for maintenance and environmental issues
are prioritized differently, and maintenance does not necessarily take place in densely populated areas.
4.1 BackgroundIn the period from 1986-2014 Banedanmark ran a noise abatement program, where all dwellingsin Denmark with a façade noise impact higher than the specified noise limit have been protected witheither noise insulation or/and noise screens. This strategy covered both noise from the track as well
as from the railway operators. In 2015, Banedanmark changed this strategy and decided to focus on
the noise from the track and wherever possible to reduce the noise at the source and not at the receivers.
The aim was to lower the cost for noise reduction and thereby to be able to lower the noise for a lot
more people but with the same economical costs. By setting higher standards for the infrastructure interms of more smooth rails with less surface defects Banedanmark as the infrastructure manager has
set a standard for the different operators which encourages them to strengthen their cooperation on
this issue and this is expected to lead towards preventive maintenance replacing remedial measures.
Some of the initiatives that have been taken have been the sharing of data from Banedanmark's
different axle load stations around Denmark aimed at making the operators improve the quality of
their wheels and the development of a management system that forces the different operators to run
with a higher wheel and load standard than before. Another initiative is the use of roughness data forprioritization and documentation of noise reducing measures.
4.2 Parameters for optimization
The prioritization tool is based on several track parameters that have a profound influence on thenoise level and on the population density along the railway. By establishing a model for the weightingof these parameters, all lines and track sections can be prioritized in relation to each other with theaim that in the case of repair/maintenance the most socio-economic noise reduction can be obtainedin the most densely populated areas.
To assess the maintenance condition on the individual line it is necessary to know the "roughnesslevel"/track quality of the average "normal situation" - where maintenance is not needed. By
comparing the measured levels on the individual lines with the “normal situation” lines with a highroughness level can be identified. In combination with knowledge of the characteristics of theinfrastructure (e.g. placing of welds, insulation joints, switches, etc.) and the cost of remediation a
reduction in noise emission relative to the repair cost can be calculated.
The following parameters must be uncovered:
1. The roughness level for the "normal situation" in general and for selected track elements
as isolated joints, switches, etc., where there will be differences as to what an acceptablelevel is.
2. The equivalent roughness level of the individual track elements – switches, crossings,
isolated joints - that will trigger maintenance, i.e., the criterion level for triggering need ofmaintenance.
3. The effect of the various maintenance methods measured as a reduction in roughness level.
Staticical analyses of all results from the first campaign in 2017 showed that the average roughnesslevel in terms of L λCA,line speed is 11.9 dB. This covers a great variation of levels – some of them up toabout 30 dB. Equivalent roughness levels for track components vary somewhat more with levels up
to as high as 45 dB in single cases.
The effect of grinding and milling has been estimated for at 100-kilometer line by comparing
roughness levels from the 2017 and 2018 campaign on sections where one of these activities had been
performed. This analysis should be extended to more lines, but the first results are shown in figure 6.

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15Reduction in LλCA,120 [dB]1050-5-100510152025

Original level of LλCA,120 [dB]
Milling

Grinding

Figure 6 – Effect of grinding and milling
Grinding and milling is typically done on track sections of a certain length and an important thing toconsider when planning maintenance is therefore to decide on the minimum section length that makes
sense from an economical point of view. As a starting point, Banedanmark has therefore chosen toaggregate data at every 100 meters length of track.
Table 1 – Parameters included in the prioritization toolParameter
Roughness

Description
Average roughness per 100 m
track section

Maximum level

Maximum level and number ofmaximum levels per 100 m
track section

Amount/mix of trains

Train length per 24 hours forpassenger and freight trains
Line speed for passenger andfreight trains
Relative density of residentialbuildings and distance to therailway

Train speed
Population density

Maintenance need

Effect of various maintenancemethods

Maintenance costs

Cost for maintenance types

Function
Input for calculating
roughness compared withthe average level
Difference from averagelevel is combined withplacement of switches orinsulations joints for
identifying critical spots
Included in thecorrection for roughness
Included in thecorrection for roughness
Distance to dwellings
combined with density
scored in relevantintervals
Scores at relevantintervals and is included
in weighting
Includes weighting
together with otherparameters1587

4.3 Implementation in GIS
The prioritization tool is implemented in GIS, where it is possible to extract information withvarious levels of details. Figure 7 is a screenshot from the GIS showing a table with the track sections
prioritized and a map where track sections are color coded according to priority.

Figure 7 – Screenshot with measured roughness weighted according to speed, traffic, density and economy
The aggregated roughness for the 100-metres sections therefore needs to be geocoded in relation
to the track theme in GIS. Data can then be combined with data relating to train types (share of freightand passenger trains) and speed of the relevant track sections, as these parameters have an impact on
the noise emitted to the surroundings.
Once the maintenance method has been selected the effect in terms of roughness reduction inrelation to economical costs and building density along the railway can be assessed and prioritized.

5. CONSEQUENCES FOR GENERAL MAINTENANCE
Besides the obvious use of data to prioritize maintenance according to rail roughness in
combination with population density these data have also proved to be of great use for planning ofgeneral maintenance (3). The data reveals a lot about the quality of the rail head surface and incombination with e.g. pictures of the railheads provided by the traditional measuring cars
Banedanmark has been able to identify a substantial amount of rail defects not detected by othermethods like e.g. ultrasound measurement. These include bad weldings, periodically spaced imprints
from wheel flats, badly isolated joints, bad switches etc. Identifying and removing these faults at an
early stage have great economic benefits.

6. SUMMARY
Over the past two years rail roughness surveys have become an important part of Banedanmark’sstrategy to reduce the environmental noise from the railway.
Staff responsible for answering noise complaints now have an efficient tool for assessing the track
condition and can give more qualified answers to complainants.
The prioritization tool described here for the socio-economic optimization of noise reducing
measures like grinding and milling etc. will ensure that the funds available for these activities areused in the most effective way. Documentation of the environmental effects of these measures is part1588

of the tool and will strengthen the arguments for prioritizing funding of these activities in politicaldecision-making.
Lastly, the roughness data have been used to plan the maintenance in terms of milling and grindingin 2019 and has also proven to be an effective tool in finding rail surface defects at an early stage
resulting in financial savings.

REFERENCES
1. ISO 3095:2013 - Acoustics - Railway applications - Measurement of noise emitted by railbound vehicles.
2. EN 15610:2009, Railway applications - Noise emission - Rail roughness measurement related to rollingnoise generation.
3. P. Dings, S. van Lier. Measurement and presentation of wheel and rail roughness. WCRR, Florence:November 1997.
4. Junge S, Svantesson S, Rodriques A, Rasmussen C. Roughness measurements in Banedanmark implications for efficient track maintenance and environmental noise reduction. IWRN13, Ghent,Belgium.

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