Acoustic Signature and Impact of High-Speed Railway Vehicles in the Vicinity of Transport Routes

Abstract

In this paper, an attempt is undertaken to identify the acoustic signature of railway vehicles travelling at 200 km/h. In the framework of conducted experimental research, test fields were determined, measurement apparatus was selected and a methodology for making measurements was specified, including the assessment of noise emission on curved and straight track for electric multiple units of Alstom type ETR610-series ED250, the so-called Pendolino. The measurements were made with the use of an acoustic camera and a 4 × 2 microphone array, including four equipped measurement points and two microphones located at the level of the head of the rail and at a height of 4 m above this level. As a result of the conducted experimental research, the dominant noise sources were identified and amplitude–frequency characteristics for these sources were determined by dividing the spectrum into one-third octave bands in the range from 20 Hz to 20 kHz. The paper also considers issues related to the verification of selected models of noise assessment in terms of their most accurate reflection of the phenomenon of propagation in close surroundings. On the basis of conducted experimental studies, the behaviour of selected models describing the change of sound level with frequency division into one-third octave bands as a function of variable distance of observer from the railway line on which high-speed railway vehicles are operated was verified. In addition, the author’s propagation model is presented together with a database built within the scope of the study, containing the actual waveforms in the time and frequency domain.

Dynamic Sustainable Processes Simulation to Study Transport Object Efficiency

“…The problem was that there was no tool for analytical modeling of physical processes inside the objects of simulation in time. Understanding that power effects in objects are transmitted by waves can be seen in many works, for instance, to identify the acoustic signature of railway vehicles [119], for simulating the vehicle-soil-track interaction phenomenon [120], to investigate the properties of elastic waves propagating in the periodic ballasted track [121], for improving the time-frequency representation for signals dedicated to structural diagnostics [122], for the application of embedded track in metro systems [123], to study the effects of wheel-rail impacts on the fatigue damage of the fastening clips at the rail joints of a high-speed railway [124], for evaluating the reliability of the dynamic performance of the vehicle [125], for the prediction of the influences of rail irregularities on the wheel/rail dynamic force [126], for studying the cause of train-induced ground vibration [127], for investigating issue of predictive maintenance by detecting possible structural failure or defects the third rail [128], to assess derailment risks [129], for simulation studies of the oscillatory behavior of road and rail vehicles [130], for advanced remote condition monitoring of railway infrastructure and rolling stock [131], for random-vibration-based on-board railway vehicle and track monitoring [132]. However, the provisions of the elastic wave theory have not been used to analytically describe the propagation of dynamic processes in space and time.…”