Urban trains running on ground surface lead to evironmental ground vibrations in the vicinity of railwaylines. The complicated vibration source of the system can hardly be measured directly. The inversion methodology ...Urban trains running on ground surface lead to evironmental ground vibrations in the vicinity of railwaylines. The complicated vibration source of the system can hardly be measured directly. The inversion methodology in engineering seismology is borrowed here to study the dynamic exciting sourec, i.e., the wheel-rail unevenness. A dynamic coupled train-track-3D ground model is combined with a genetic algorithm for the inversion. The solution space of the inversion variables, the objective function and the solving genetic strategy of the inversion are determined, and a joint inversion for the wheel-rail unevenness source function and some track structure parameters is therefore designed. The wheel-rail unevenness PSD, being the source function of No. 13 Beijing urban railway, is obtained by the inversoin based on observed data in the field. The result indicates that the source function discribes the track unevenness in the range of wavelength over 1.2 m, and reflects properly wheel irregularites in the range of wavelength shorter than 1.2 m. It should be noticed that the urban rail traffic is not very fast, and this range of short wavelength is exactly corresponding to the main frequency band of environmental vibrations from the traffic. The unevenness of wavelength under 1.2 m is underestimated, and the ground vibration in the main frequency band must be underestimated consequently, if the track unevenness spectrum is taken as the source function. Rather than the track spectrum reflecting just the evenness of track, the wheel-rail spectrum expresses both the track unevenness and the irregularities of wheels, and therefore is more suitable to be the source function of urban railway traffic. It is also convinced that the exciting source inversion according to observed ground vibrations is an effective way to detect quantitatively the combined wheel-rail unevenness.展开更多
基金supported by the National Natural Science Foundation of China (Grant No. 50538030)
文摘Urban trains running on ground surface lead to evironmental ground vibrations in the vicinity of railwaylines. The complicated vibration source of the system can hardly be measured directly. The inversion methodology in engineering seismology is borrowed here to study the dynamic exciting sourec, i.e., the wheel-rail unevenness. A dynamic coupled train-track-3D ground model is combined with a genetic algorithm for the inversion. The solution space of the inversion variables, the objective function and the solving genetic strategy of the inversion are determined, and a joint inversion for the wheel-rail unevenness source function and some track structure parameters is therefore designed. The wheel-rail unevenness PSD, being the source function of No. 13 Beijing urban railway, is obtained by the inversoin based on observed data in the field. The result indicates that the source function discribes the track unevenness in the range of wavelength over 1.2 m, and reflects properly wheel irregularites in the range of wavelength shorter than 1.2 m. It should be noticed that the urban rail traffic is not very fast, and this range of short wavelength is exactly corresponding to the main frequency band of environmental vibrations from the traffic. The unevenness of wavelength under 1.2 m is underestimated, and the ground vibration in the main frequency band must be underestimated consequently, if the track unevenness spectrum is taken as the source function. Rather than the track spectrum reflecting just the evenness of track, the wheel-rail spectrum expresses both the track unevenness and the irregularities of wheels, and therefore is more suitable to be the source function of urban railway traffic. It is also convinced that the exciting source inversion according to observed ground vibrations is an effective way to detect quantitatively the combined wheel-rail unevenness.
