Vol 54, No 2 (2018)

A homogeneous fine-grained structure that provides required strength characteristics has been shown to form in the (44NKhTYu alloy) elinvar for the considered thermal processing mode. Experimental data are provided that demonstrate elasticity characteristics to remain constant within a temperature range from–70 to +70°С. The persistence of the propagation velocities of elastic waves in this temperature range makes it possible to use this regularity in the development of techniques for thermal-processing quality evaluation. The ratio of the velocities of longitudinal and shear elastic waves has been proposed as a “diagnostic parameter.” The possibility has been studied for using elastic waves to inspect 44NKhTYu-alloy characteristics after various thermal-processing modes.

The relevance of being able to detect flaws beneath horizontal exfoliations in rails with simultaneous measurement of crack parameters has been shown. Based on the performed research, the authors proposed a new method for revealing transverse cracks (including beneath surface damages) in railheads and evaluating their parameters. The method is based on a multichannel implementation of ultrasonic through-transmission inspection and on processing of the results of layerwise scanning of a tested rail section. Pilot field tests with a new defectoscope that implements the proposed method have shown that the device is capable of revealing the above flaws in railheads, with the measurement error not exceeding 15%.

The current methods for evaluating the phase composition of austenitic steels that, in addition to austenite, may also contain the phase of ferrite or martensite or both are considered. The possibilities offered by destructive and nondestructive testing techniques are compared.

The dynamic effect of a free molecular effusion-type flow from a leak on a microfiber sensor in the form of a spherical conglomerate of equiprobably spatially oriented fibers with their low volume concentration has been studied. An estimate of how the size effect (the ratio of the microfiber sensor radius to a characteristic linear dimension of the problem) influences the sensor dynamics is provided.

Micro defects usually lead to performance degradation of materials. Pulse-echo technique is an effective method of revealing micro defects in materials, and booming in which has been witnessed over the years. However, detection of flaw echoes submerged in intensive noise is challenging. In this paper, a method of flaw echoes detection based on generalized S-transform is proposed. The original signals are transformed to time-frequency domain by generalized S-transform in the first stage. Subsequently, the time-frequency spectrums are enhanced through image segmentation techniques, including global thresholding and dilation. Finally, clear flaw echoes are obtained by inverse generalized S-transform, contributing to further investigation of defects. Both the simulation and experimental results show effectiveness of the flaw echoes detection method.