Safety Certificate: an audification performance of high-speed trains

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<ul><li><p>OPEN FORUM</p><p>Safety Certificate: an audification performance of high-speedtrains</p><p>Florian Grond</p><p>Received: 13 November 2010 / Accepted: 9 August 2011 / Published online: 26 August 2011</p><p> Springer-Verlag London Limited 2011</p><p>Abstract Safety Certificate is a musical performance</p><p>based on sensor data from high-speed trains. The original</p><p>purpose of this data is to provide a basis for the assess-</p><p>ments of the mechanical aspects of train safety. In this</p><p>performance, the data, which represents dynamical pro-</p><p>cesses below the audible range, are converted into sound</p><p>through audification. The sound that is generated live</p><p>during the performance is manipulated through the Manta</p><p>control interface, which allows for the convenient layering</p><p>of 48 different timbres. Safety Certificate was premiered at</p><p>Seconde Nature in Aix-en-Provence in March 2010 during</p><p>the Sonification symposiumWhat, Where, How, Why,</p><p>organized by Locus Sonus. The following short article</p><p>gives details about the data, the audification technique, use</p><p>of the control interface, and the musical structure of the</p><p>performance.</p><p>Keywords Audification Performance</p><p>1 Introduction</p><p>Traveling with trains is an experience that has always had a</p><p>strong acoustic dimension. Sonic associations of trains can</p><p>be as old fashioned as the steam blow from a nineteenth</p><p>century train, or more subtle like the characteristic repeti-</p><p>tive sound of the wheel hitting the gap between two joint</p><p>rails. Today, the comfort of traveling in the acoustically</p><p>well-insulated wagons of high-speed trains has deprived us</p><p>of many of those sonic experiences.</p><p>In the sonification discourse, it has often been argued</p><p>that listening is a powerful way of assessing the proper</p><p>functioning of mechanical devices. In practice, technicians</p><p>often use their listening skills as a diagnostic device before</p><p>disassembling an engine. This inference based on acoustic</p><p>cues is also similar to medical diagnosis that is done by</p><p>listening to a patients chest.</p><p>High-speed trains need to undergo intensive testing</p><p>during the homologation process, before they are approved</p><p>for public service. This process entails the collection of</p><p>data from measurements of the mechanical parts of the</p><p>train. Interestingly, it is not only the train passengers who</p><p>hear little of the vehicle transporting them; technicians who</p><p>measure and maintain the trains also rely almost exclu-</p><p>sively on vision. Assessment of the wear of mechanical</p><p>parts of the train, such as wheels and axles, is an involved</p><p>process, and the interpretation of results relies on the visual</p><p>representation of charts and numbers. Listening to mea-</p><p>surement data, however, can reveal a great deal about the</p><p>forces that act onto the mechanical parts and their dynamic</p><p>response. In the data used in this performance, the slow</p><p>rocking movement of a wagon going at constant speed or</p><p>the harsh force of the brakes, when the train decelerates,</p><p>can be clearly heard. This suggests that an auditory display</p><p>of these data might have benefits for monitoring purposes.</p><p>2 The data</p><p>Data used in this performance are measurements from</p><p>sensors, which are attached to mechanical parts of high-</p><p>speed trains. These data are usually used as the basis of</p><p>subsequent sophisticated simulations, which allow</p><p>F. Grond (&amp;)CITEC Cognitive Interaction Technology</p><p>Centre of Excellence, Bielefeld University,</p><p>Universtatsstrasse 21-23, 33615 Bielefed, Germany</p><p>e-mail:</p><p>123</p><p>AI &amp; Soc (2012) 27:293295</p><p>DOI 10.1007/s00146-011-0351-5</p></li><li><p>conclusions to be drawn about the durability of important</p><p>parts critical for the safety of the train. For Safety Certifi-</p><p>cate, three different data channels were used.</p><p>The first data channel corresponds to the sensor mea-</p><p>suring the vertical acceleration of the wheel. This sensor is</p><p>directly attached to the axle box. The second channel is the</p><p>measurement of the vertical displacement of the wheel. This</p><p>up and down movement corresponds to the extension of the</p><p>shocks of the wheel suspension. The third data channel is</p><p>the rotation around the vertical axis of the wagon. This can</p><p>be though of as the movement of a reversed pendulum</p><p>pointing from the rails up. The first data channel is partic-</p><p>ularly interesting, since the axle box has no suspension and</p><p>hence has to directly absorb all forces acting on the wheel.</p><p>While sitting in the wagon, a passenger is removed from</p><p>this direct impact by two layers of suspension.</p><p>The data are all originally recorded at 1,200 Hz and are</p><p>low-pass filtered at 300 Hz, because for the homology</p><p>process and dynamic processes in this frequency range are</p><p>of interest. This low-frequency range is due to the fact that</p><p>that the moving parts of trains have a heavy mass, and</p><p>therefore can only oscillate within low frequencies. The</p><p>highest perceived frequencies of dynamical phenomena</p><p>captured by these data appeared to be oscillations of 60 Hz.</p><p>The average frequency is, however, much lower and the</p><p>biggest part of the data, therefore, lie in a very subfrequent,</p><p>almost inaudible range.</p><p>3 Audification</p><p>The subfrequency data from real physical processes as</p><p>described above are an ideal candidate for audification.</p><p>Among all sonification techniques, audification is the most</p><p>direct conversion of data into sound.</p><p>More specifically, the data is loaded into a buffer and the</p><p>only further data transformation is amplitude normalization.</p><p>Data in the buffer is then played directly by sending it to the</p><p>digital to audio converter. The most important degree of</p><p>freedom for manipulating the sound in audification is the</p><p>change of playback speed. This is in fact necessary since the</p><p>processes measured from the trains are not happening on a</p><p>time scale that would lead to sound signals within the</p><p>human audible range. Data from the sensor that was directly</p><p>attached to the axle box was the primary source for audi-</p><p>fication, since it contained the most sonically interesting</p><p>features. The other two channels were used to control the</p><p>spatialization of the sound. For the purpose of spatialization</p><p>in the stereo field, the playback speed differed from that</p><p>used for audification. Hence, the movement of the sound</p><p>was not synchronous with the audification itself. This</p><p>artistic intervention was necessary in order for the spatial-</p><p>ization of the sound to take place at perceivable speed.</p><p>4 The control interface</p><p>For the real-time control of the sound during the perfor-</p><p>mance, I used the Manta,1 a touch-sensitive interface for</p><p>controlling music or video. The Manta consists of 48</p><p>sensors in a hexagonal array. These sensors measure</p><p>the resistance of the skin, which can be modulated by the</p><p>surface area your finger is covering. The sensors of the</p><p>touch-sensitive interface also features LED backlighting,</p><p>which, when activated, provides the performer with visual</p><p>feedback. For the audience, this backlighting evoked the</p><p>illusion of a real desk in a control center, where many</p><p>trains are simultaneously monitored. A photo of the inter-</p><p>face as used during the performance is depicted in Fig. 1.</p><p>For sound synthesis, the Manta was connected to Super-</p><p>Collider McCartney (1996). Each of the 48 sensors on the</p><p>interface controlled the volume of one audificationall 48</p><p>playing simultaneously. Each audification is tuned to a</p><p>different playback speed. The playback speed was loga-</p><p>rithmically mapped between the original data rate to a 5</p><p>times that rate, taking into account the non-linear relation</p><p>of frequency to pitch. In addition to the panning defined by</p><p>data, the amplitude of playback was modulated via sensor</p><p>values of the Manta. Low pressure leads to less volume and</p><p>more spatial movement, whereas strong pressure meant</p><p>louder playback with almost no stereo panning.</p><p>5 The performance</p><p>Safety Certificate stands in the long tradition of using train-</p><p>related sounds for music, for instance, the Mouvement</p><p>Symphonique Pacific 231 by Arthur Honegger or the Etude</p><p>aux Chemins de Fer by Pierre Schaeffer. Inspired by these</p><p>classic works, the performance follows the structure of a</p><p>Fig. 1 The control interface Manta used by the author during theconcert in Aix-en-Provence</p><p>1 The Manta is build by Jeff Snyder see http://www.snyder</p><p></p><p>294 AI &amp; Soc (2012) 27:293295</p><p>123</p></li><li><p>sonata movement. I usually inform the audience that they</p><p>will be listening to data, without specifying their origin.</p><p>The audience know that they hear first the data at two</p><p>times the original speed, in classical terms, this corre-</p><p>sponds to the exposition of the theme. I chose not to use the</p><p>original playback speed in the exposition, because this very</p><p>slow playback causes some very deep and often-unnoticed</p><p>rumbles in the subfrequency range, an experience that can</p><p>be better appreciated after familiarization, through careful</p><p>listening, to the audification of the data. This is why I put</p><p>the original playback speed at the end of the performance,</p><p>when the theme will be recapitulated.</p><p>The development of the theme starts at low frequencies</p><p>and successively layers different playback speeds resulting</p><p>in an ever-changing configuration of timbres. As mentioned</p><p>above, slow playback speeds tend to produce subaudio</p><p>frequencies, and it is only if one knows the origin of the data</p><p>that any similarity with the almost inaudible rocking</p><p>movement of trains can be perceived. At medium playback</p><p>speed, the sound is more reminiscent of a train. When it is</p><p>speeded up even further, the data sounds like a ski lift and</p><p>then like a tiny clockwork mechanism. The surprising</p><p>variety of different timbres that arise from the audification</p><p>of these data sets is the material for the musical counter-</p><p>point during the developments of the theme.</p><p>6 Conclusion</p><p>Safety Certificate is a life performance that combines</p><p>technological information from high-speed trains with</p><p>classical musical forms. Live audification together with an</p><p>esthetically appealing control interface proved to be a</p><p>successful combination in terms of creating an evocative</p><p>experience through the performance. Beyond this, the</p><p>surprising richness of the sounds produced suggest that</p><p>audification of the data might be useful for the monitoring</p><p>of mechanical train parts.</p><p>Acknowledgments The author would like to thank Fabian Schmidfrom PJ Messtechnik ( for providing the data of</p><p>the high-speed trains. Till Bovermann gave me a very useful intro-</p><p>duction howto program the Manta interface, which is a SuperColliderclass implemented by Alberto deCampo.</p><p>Reference</p><p>McCartney J (1996) Supercollider: a new real-time synthesis</p><p>language. In: Proceedings of international computer music con-</p><p>ference (ICMC96), pp 257258</p><p>AI &amp; Soc (2012) 27:293295 295</p><p>123</p><p>Safety Certificate: an audification performance of high-speed trainsAbstractIntroductionThe dataAudificationThe control interfaceThe performanceConclusionAcknowledgmentsReference</p></li></ul>


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