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The heat flux density of solar radiation, received by each surface of a double-block ballastless track bed slab, is closely related to its alignment and geographical latitude. In this work, a temperature field analysis model based on experimental data, the theories of solar radiation, and boundary heat transfer is established by a CRTS-I double-block ballastless track structure using the ABAQUS finite element software to investigate the influence of different alignments and geographical latitudes of the temperature field. The horizontal and vertical temperature gradients of the ballast bed plate were found to be in the most adverse conditions when the angle a n between the normal direction of the ballastless track slab bedside surface and positive south direction was equal to 90°. The standard deviation of the overall temperature gradient of the ballast bed was found to be at lowest and standard value of the dispersion degree was highest at an a n of 90°: 14.138 and 10.446°C/m, respectively. The horizontal and vertical temperature gradients in high latitudes and coastal areas were found to be more detrimental than that in the low latitudes or inland areas. These results can provide references for how to avoid high-temperature loading during railway line selection and track design.

Defect detection in ferromagnetic substrates is often hampered by nonmagnetic coating thickness variation when using conventional eddy current testing technique. The lift-off distance between the sample and the sensor is one of the main obstacles for the thickness measurement of nonmagnetic coatings on ferromagnetic substrates when using the eddy current testing technique. Based on the eddy current thin-skin effect and the lift-off insensitive inductance (LII), a simplified iterative algorithm is proposed for reducing the lift-off variation effect using a multifrequency sensor. Compared to the previous techniques on compensating the lift-off error (e.g., the lift-off point of intersection) while retrieving the thickness, the simplified inductance algorithms avoid the computation burden of integration, which are used as embedded algorithms for the online retrieval of lift-offs via each frequency channel. The LII is determined by the dimension and geometry of the sensor, thus eliminating the need for empirical calibration. The method is validated by means of experimental measurements of the inductance of coatings with different materials and thicknesses on ferrous substrates (dual-phase alloy). The error of the calculated coating thickness has been controlled to within 3% for an extended lift-off range of up to 10 mm.

Lift-offs of the sensor could significantly affect the measurement signal and reconstruction of material properties when using the electromagnetic (inductive) eddy current (EC) sensor. Previously, various methods (including novel sensor designs, and features like zero-crossing frequency, lift-off point of intercept) have been used for eliminating the measurement error caused by the lift-off distance effect of the sensor. However, these approaches can only be applied for a small range of lift-off variations. In this article, a linear relationship has been found between the sensor lift-off and ratio of dual-frequency EC signals, particularly under the high working dual frequencies. Based on this linear relationship, the lift-off variation can be reconstructed first with a small error of 2.5% when its actual value is up to 10 mm (10.1% for 20 mm). The reconstructed lift-off is used to further get the property of the material under a low single frequency. Experiments on different ferrous metals have been carried out for the testing of the reconstruction scheme. Since the inductance is more sensitive to the material property (and less sensitive to the lift-off) under low frequencies, the reconstruction error of the material property is much smaller than that of the lift-off, with 1.4% under 12 mm (and 4.5% under 20 mm).