The degradation of the railway subgrade is a common cause for train accidents in Russia because of the extensive railway system and large areas of weak soils. We present a seismic monitoring technique that utilizes moving trains as signal sources to probe the properties of the subgrade. The broadband (periods up to 100 s) seismic sensors recorded signals over several weeks during a non-stop monitoring experiment. The large statistic allows us to identify the signals properties and thus these signals are processed by an automated system. We defined the parameters of the low-frequency signal generated by a passing train that are sensitive to changes in the subgrade state. These are the ratio of amplitudes of horizontal components, and the time interval between the end of the train passage and the maximum amplitude surge in the component transversal to rails. We propose an analytical model to describe the interaction between a moving train and the subgrade that takes into consideration the viscosity of a substrate layer. The application of this model produces a consistent explanation of processes in the media and enables an “in situ” estimation of soil elasticity and viscosity, caused by seasonal thawing.

No abstract

Changes in the elastic characteristics of the railway subgrade have been determined using nonstop long-term (more than 50 days) train passage seismic observations. We examined the records of the broadband sensitive seismometer TC-120s in the low-frequency band (below 0.1 Hz) to obtain the subgrade response to various train passages and its relaxation after unloading. Analytical models of subgrade deformation by the train are proposed. When comparing models in the experiment, we showed that a lowpass filter (below 0.1 Hz) provides waveforms with parameters determined by the deformation properties of the soil. We carried out statistical processing of 1600 train seismic records and determined parameters characterizing the subgrade reaction to the vibration effects created by trains in the ultra-low-frequency range. Therefore, we can use these parameters to monitor after daily averaging and weekly smoothing. When observing the spring thawing of the soil, we considered the sensitivity of seismic monitoring using heavy vehicle vibrations, particularly changes in the soil state properties under a rise in ambient temperature. The presented observations can be used for seismic monitoring technology at an early stage of hazardous processes in the subgrade.