Railway track maintenance is becoming a challenge for Railway Engineers due to the need of meeting increasingly high quality requirements by means of cost-effective procedures. This can be only achieved by implementing some technological developments from other fields into the railway sector, such as Digital Signal Processing. Indeed, the present project delves into data acquisition and processing techniques in order to enhance track surveying processes. In particular, the project is based on train/track dynamic interaction through the gathering and subsequent analysis of axlebox accelerations. For this purpose, the accelerations produced while trains run are gathered and analysed in different ways: varying sampling and filtering frequencies, the location of accelerometers along the train and the different parameters that define some time-frequency representations.

The obtained results show the optimal values for train/track dynamic interaction as well as the best location for the accelerometers. In addition, it is demonstrated that, through spectral analysis and time-frequency diagrams, it is possible to identify and classify diverse track defects, track singularities and vibration modes laying the foundations for the application of digital image processing techniques to railway track maintenance.

Once the different track aspects have been detected and classified, it is also possible to monitor the evolution of the maintenance conditions track geometry and its components.