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The fast, convenient, and accurate determination of railroad cars' load mass is critical to ensure safety and allow asset counting in railway infrastructure. In this paper, we propose a method for modeling the mechanical deformations that occur in the rail web under the influence of a static load transmitted through a railway wheel. According to the proposed method, a railroad car's weight can be determined from the rail deformation values. A solid model of a track section, including a railroad tie, rail, and wheel, is developed, and a multi-physics simulation technique that allows for the determination of the values of deformations and mechanical stresses in the strain gauge installation areas is presented. The influence of the loaded mass, the temperature of the rail, and the wheel position relative to the strain gauge location is considered. We also consider the possibility of using artificial neural networks to determine railroad cars' weight without specifying the coordinates of the wheel position. The effect of noise in the data on the accuracy of determining the railroad car weight is considered. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for monitoring surface defects like cracks in highly loaded structures. This method is based on the ability of surface cracks to open under the influence of external loads, thus causing the appearance of stresses and tears in the sensitive element—thin films that were deposited on the surface of the test object. We developed a system for monitoring surface defects based on a distributed crack sensor, the functional scheme of the sensor and its design, the structural scheme and algorithm of the system operation, and its model as a VHDL (VHSIC (Very high speed integrated circuits) Hardware Description Language)-description. [ABSTRACT FROM AUTHOR]