Residual stress, a factor affecting the fatigue and fracture characteristics of rails, is formed during the processes of fabrication and heat treatment, and is also generated by vertical loads on wheels due to the weight of vehicles. Moreover, damage to rails tends to accelerate due to the continuous increase in the number of passes and to the high speed of passing vehicles. Because this can have a direct effect on safety accidents, having a technique to evaluate and analyze the residual stresses in rails accurately is very important. In this study, stresses due to tensile loads applied to new rails and residual stresses remaining in used rails were measured by using magnetic Barkhausen noise method. First, a magnetization frequency and noise band suitable for the rails were selected. Moreover, by applying tensile loads to specimens and comparing the difference in magnetization amplitudes for each load, the stresses applied to the rails by using the magnetic Barkhausen noise method were measured, and the analysis of the results was verified. Based on these results, the difference in the results for the loads asymmetrically applied according to the wheel shape was analyzed by measuring for the head parts of used rails.

Liquefied hydrogen storage vessels (LHSVs) are vulnerable to surface-crack initiation, propagation, and fracture on their surfaces because they are under high-pressure, low-temperature conditions. Defects can also occur in the coatings of the storage containers used to prevent hydrogen permeation, and these lead to surface defects such as pitting corrosions. Together, these increase the probability of liquid hydrogen leaks and can cause serious accidents. Therefore, it is important to detect surface defects during periodic surface inspections of LHSVs. Among the candidate non-destructive evaluation (NDE) techniques, testing using guided waves (GWs) is effective for detecting surface defects. Because of the ability of GWs to travel long distances without significant acoustic attenuation, GW testing has attracted much attention as a promising structural monitoring technique for LHSVs. In this study, an ultrasonic NDE method was designed for detecting surface defects of 304SS plate, which is the main material used for fabricating LHSVs. It involves the use of linear discriminant analysis (LDA) based on short-time Fourier transform (STFT) pixel information produced from GW data. To accomplish this, the differences in the number of STFT pixels between sound and defective specimens were used as a major factor in distinguishing the two groups. Consequently, surface defects could be detected and classified with 97% accuracy by the newly developed pixel-based mapping method. This indicates that the newly developed NDE method with LDA can be used to detect defects and classify LHSVs as either sound or defective.