OPEN FORUM

Safety Certificate: an audification performance of high-speedtrains

Florian Grond

Received: 13 November 2010 / Accepted: 9 August 2011 / Published online: 26 August 2011

� Springer-Verlag London Limited 2011

Abstract Safety Certificate is a musical performance

based on sensor data from high-speed trains. The original

purpose of this data is to provide a basis for the assess-

ments of the mechanical aspects of train safety. In this

performance, the data, which represents dynamical pro-

cesses below the audible range, are converted into sound

through audification. The sound that is generated live

during the performance is manipulated through the Manta

control interface, which allows for the convenient layering

of 48 different timbres. Safety Certificate was premiered at

Seconde Nature in Aix-en-Provence in March 2010 during

the Sonification symposium–What, Where, How, Why,

organized by Locus Sonus. The following short article

gives details about the data, the audification technique, use

of the control interface, and the musical structure of the

performance.

Keywords Audification � Performance

1 Introduction

Traveling with trains is an experience that has always had a

strong acoustic dimension. Sonic associations of trains can

be as old fashioned as the steam blow from a nineteenth

century train, or more subtle like the characteristic repeti-

tive sound of the wheel hitting the gap between two joint

rails. Today, the comfort of traveling in the acoustically

well-insulated wagons of high-speed trains has deprived us

of many of those sonic experiences.

In the sonification discourse, it has often been argued

that listening is a powerful way of assessing the proper

functioning of mechanical devices. In practice, technicians

often use their listening skills as a diagnostic device before

disassembling an engine. This inference based on acoustic

cues is also similar to medical diagnosis that is done by

listening to a patient’s chest.

High-speed trains need to undergo intensive testing

during the homologation process, before they are approved

for public service. This process entails the collection of

data from measurements of the mechanical parts of the

train. Interestingly, it is not only the train passengers who

hear little of the vehicle transporting them; technicians who

measure and maintain the trains also rely almost exclu-

sively on vision. Assessment of the wear of mechanical

parts of the train, such as wheels and axles, is an involved

process, and the interpretation of results relies on the visual

representation of charts and numbers. Listening to mea-

surement data, however, can reveal a great deal about the

forces that act onto the mechanical parts and their dynamic

response. In the data used in this performance, the slow

rocking movement of a wagon going at constant speed or

the harsh force of the brakes, when the train decelerates,

can be clearly heard. This suggests that an auditory display

of these data might have benefits for monitoring purposes.

2 The data

Data used in this performance are measurements from

sensors, which are attached to mechanical parts of high-

speed trains. These data are usually used as the basis of

subsequent sophisticated simulations, which allow

F. Grond (&)

CITEC Cognitive Interaction Technology

Centre of Excellence, Bielefeld University,

Universtatsstrasse 21-23, 33615 Bielefed, Germany

e-mail: fgrond@techfak.uni-bielefeld.de

123

AI & Soc (2012) 27:293–295

DOI 10.1007/s00146-011-0351-5

conclusions to be drawn about the durability of important

parts critical for the safety of the train. For Safety Certifi-

cate, three different data channels were used.

The first data channel corresponds to the sensor mea-

suring the vertical acceleration of the wheel. This sensor is

directly attached to the axle box. The second channel is the

measurement of the vertical displacement of the wheel. This

up and down movement corresponds to the extension of the

shocks of the wheel suspension. The third data channel is

the rotation around the vertical axis of the wagon. This can

be though of as the movement of a reversed pendulum

pointing from the rails up. The first data channel is partic-

ularly interesting, since the axle box has no suspension and

hence has to directly absorb all forces acting on the wheel.

While sitting in the wagon, a passenger is removed from

this direct impact by two layers of suspension.

The data are all originally recorded at 1,200 Hz and are

low-pass filtered at 300 Hz, because for the homology

process and dynamic processes in this frequency range are

of interest. This low-frequency range is due to the fact that

that the moving parts of trains have a heavy mass, and

therefore can only oscillate within low frequencies. The

highest perceived frequencies of dynamical phenomena

captured by these data appeared to be oscillations of 60 Hz.

The average frequency is, however, much lower and the

biggest part of the data, therefore, lie in a very subfrequent,

almost inaudible range.

3 Audification

The subfrequency data from real physical processes as

described above are an ideal candidate for audification.

Among all sonification techniques, audification is the most

direct conversion of data into sound.

More specifically, the data is loaded into a buffer and the

only further data transformation is amplitude normalization.

Data in the buffer is then played directly by sending it to the

digital to audio converter. The most important degree of

freedom for manipulating the sound in audification is the

change of playback speed. This is in fact necessary since the

processes measured from the trains are not happening on a

time scale that would lead to sound signals within the

human audible range. Data from the sensor that was directly

attached to the axle box was the primary source for audi-

fication, since it contained the most sonically interesting

features. The other two channels were used to control the

spatialization of the sound. For the purpose of spatialization

in the stereo field, the playback speed differed from that

used for audification. Hence, the movement of the sound

was not synchronous with the audification itself. This

artistic intervention was necessary in order for the spatial-

ization of the sound to take place at perceivable speed.

4 The control interface

For the real-time control of the sound during the perfor-

mance, I used the Manta,1 a touch-sensitive interface for

controlling music or video. The Manta consists of 48

sensors in a hexagonal array. These sensors measure

the resistance of the skin, which can be modulated by the

surface area your finger is covering. The sensors of the

touch-sensitive interface also features LED backlighting,

which, when activated, provides the performer with visual

feedback. For the audience, this backlighting evoked the

illusion of a real desk in a control center, where many

trains are simultaneously monitored. A photo of the inter-

face as used during the performance is depicted in Fig. 1.

For sound synthesis, the Manta was connected to Super-

Collider McCartney (1996). Each of the 48 sensors on the

interface controlled the volume of one audification–all 48

playing simultaneously. Each audification is tuned to a

different playback speed. The playback speed was loga-

rithmically mapped between the original data rate to a 5

times that rate, taking into account the non-linear relation

of frequency to pitch. In addition to the panning defined by

data, the amplitude of playback was modulated via sensor

values of the Manta. Low pressure leads to less volume and

more spatial movement, whereas strong pressure meant

louder playback with almost no stereo panning.

5 The performance

Safety Certificate stands in the long tradition of using train-

related sounds for music, for instance, the Mouvement

Symphonique Pacific 231 by Arthur Honegger or the Etude

aux Chemins de Fer by Pierre Schaeffer. Inspired by these

classic works, the performance follows the structure of a

Fig. 1 The control interface Manta used by the author during the

concert in Aix-en-Provence

1 The Manta is build by Jeff Snyder see http://www.snyder

phonics.com/.

294 AI & Soc (2012) 27:293–295

123

sonata movement. I usually inform the audience that they

will be listening to data, without specifying their origin.

The audience know that they hear first the data at two

times the original speed, in classical terms, this corre-

sponds to the exposition of the theme. I chose not to use the

original playback speed in the exposition, because this very

slow playback causes some very deep and often-unnoticed

rumbles in the subfrequency range, an experience that can

be better appreciated after familiarization, through careful

listening, to the audification of the data. This is why I put

the original playback speed at the end of the performance,

when the theme will be recapitulated.

The development of the theme starts at low frequencies

and successively layers different playback speeds resulting

in an ever-changing configuration of timbres. As mentioned

above, slow playback speeds tend to produce subaudio

frequencies, and it is only if one knows the origin of the data

that any similarity with the almost inaudible rocking

movement of trains can be perceived. At medium playback

speed, the sound is more reminiscent of a train. When it is

speeded up even further, the data sounds like a ski lift and

then like a tiny clockwork mechanism. The surprising

variety of different timbres that arise from the audification

of these data sets is the material for the musical counter-

point during the developments of the theme.

6 Conclusion

Safety Certificate is a life performance that combines

technological information from high-speed trains with

classical musical forms. Live audification together with an

esthetically appealing control interface proved to be a

successful combination in terms of creating an evocative

experience through the performance. Beyond this, the

surprising richness of the sounds produced suggest that

audification of the data might be useful for the monitoring

of mechanical train parts.

Acknowledgments The author would like to thank Fabian Schmid

from PJ Messtechnik (http://www.pjm.co.at) for providing the data of

the high-speed trains. Till Bovermann gave me a very useful intro-

duction howto program the Manta interface, which is a SuperCollider

class implemented by Alberto deCampo.

Reference

McCartney J (1996) Supercollider: a new real-time synthesis

language. In: Proceedings of international computer music con-

ference (ICMC’96), pp 257–258

AI & Soc (2012) 27:293–295 295

123