Abstract
Urban rail transit is an effective way to deal with the problem of traffic congestion in major cities. Trains travel through dense residential and commercial areas, providing convenient transportation while also result in vibration problems in the surrounding environment. Long‐lasting vibrations result in disturbance to people’s sleep, malfunction of sensitive equipment, and even damage to heritage buildings. Compared with elevated and tunnel sections, ground surface urban railway generates vibrations and propagates to the surroundings via a more direct path in the form of surface waves, which makes the environmental problem more prominent. Due to the complexity of the train‐track‐ground system, the characteristics of the vibration propagation and attenuation are yet to be revealed. In this paper, we investigate the vibration of the ground and the subgrade next to the Beijing Urban Rail Line 13 by a field measurement combined with a mathematical model. The duration of ground vibration is divided into two parts: the train passing time and the Doppler effect‐related tailing part. Through a regression analysis of the duration, the train passing time is identified and the train traveling speed is estimated. The attenuation relationship of ground vibration intensity is expressed by a piecewise function. In the subgrade, the vibration intensity of particle decays with increasing depth and the stress decay rate is faster than that of the acceleration. The dynamic wheel/rail interaction behaves stationary and periodic, and the magnitude fluctuates up and down with the quasi‐static axle weight. The intensity attenuation relationship fitted in this paper provides a basis for designing new lines and renewing old lines and can be used as a reference for the development of vibration‐reduction technology. The simulated time history of the wheel‐rail force provides an excitation sample for further model experiments and numerical simulation. The proposed train speed identification method may be useful for parameter identification of moving sources such as ships, automobiles, and airplanes.
Highlights
Urban rail transit is an effective way to deal with the problem of traffic congestion in major cities
We investigate the vibration of the ground and the subgrade next to the Beijing Urban Rail Line 13 by a field measurement combined with a mathematical model. e duration of ground vibration is divided into two parts: the train passing time and the Doppler effect-related tailing part. rough a regression analysis of the duration, the train passing time is identified and the train traveling speed is estimated. e attenuation relationship of ground vibration intensity is expressed by a piecewise function
It is undoubtedly necessary to conduct in situ measurements, theoretical analyses, and numerical simulations to investigate the dominant frequency bands and spatial distribution characteristics of the ground vibration. e results may provide an essential basis for the prediction of the vibration when planning new lines and provide a necessary reference for developing the vibration isolation when updating existing lines
Summary
According to the Fourier series theory, the wheel/rail irregularity in Figure 2 can be decomposed into a series of harmonic unevenness. By the inverse Fourier transform of the spectra with respect to ω, we obtain the stochastic responses in the time domain. To verify the mathematical model above, we simulate the ground vibration at the five observation points of the in situ test. E acceleration time histories of the model output are well consistent with the observed data, both in terms of amplitude and duration. Ese results show the reliable performance of the mathematical model of the coupled train-track-ground vibration in the time domain. To further compare the frequency domain results, the time histories are converted to the vibration acceleration level (VAL) according to the Chinese national standard Urban Regional Environmental Vibration Measurement. For the vibration level above 1.6 Hz, though, the numerical results are close to the experimental results at all the measurement points
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