Block-parametric approach to non-destructive control data analysis of railroad layered foundations

Abstract

The evaluation of the parameters of multi-layered foundations (ballast prisms, railroad basis, foundations of railway structures, etc.) plays an important role in ensuring the safe movement of trains. In the last decades new equipment arrived intended for non-destructive monitoring and estimating of the condition of such structures. These instruments can combine the high speed of scanning the diagnosed surface with high measurement accuracy of scanned parameters. But the use of similar equipment requires sophisticated methods for control data analysis including the building of adequate mathematical model of considered structure, efficient methods of discretization and forward problem solving, inverse problem analysis and based on such analysis surrogate model development for online data treatment, scanned by high-speed deflectometers or other scanning equipment. Presented paper devoted to the most important part of this chain of data processing procedures, namely the inverse problem analysis. The proposed approach is based on informational-probabilistic approach for inverse problem analysis, whose task is to obtain a posteriori probability density in the space of unknown parameters. The essence of the approach is the block-parametric approximation of the a priori probability density and likelihood function in the space of parameters and model data of the problem. The method allows estimating the parameters of the a priori distribution of unknown variable parameters, identifying and excluding outliers of the measured data from the created model, and constructing a posteriori estimation of the unknown parameters’ probability density with acceptable resolution. Proposed method can be used to create a new generation of equipment intended for non-destructive monitoring and estimating of the condition of the railroad basis and other roadbed structures. The appropriate software of such equipment based on the developed methods of data processing can be developed. The use of such equipment allows to operatively analyzing the state of individual areas of the railroad to decide on the need of repairing or replacing the railroad base or foundation of other elements of railroad infrastructure.