Abstract

The micro- and macroscopic fatigue crack growth (FCG) rates of a wide class of structural materials were analyzed and it was concluded that both rates coincide either during high-temperature tests or at high stress intensity factor (SIF) values. Their coincidence requires a high level of cyclic deformation of the metal along the entire crack front as a necessary condition for the formation of fatigue striations (FS). Based on the analysis of digital fractographic images of the fatigue fracture surfaces, a method for the quantitative assessment of the spacing of FS has been developed. The method includes the detection of FS by binarization of the image based on the principle of local minima, rotation of the highlighted fragments of the image using the Hough transform, and the calculation of the distances between continuous lines. The method was tested on 34KhN3M steel in the initial state and after long-term operation (~3 × 105 h) in the rotor disk of a steam turbine at a thermal power plant (TPP). Good agreement was confirmed between FCG rates (both macro and microscopic, determined manually or using digital imaging techniques) at high SIF ranges and their noticeable discrepancy at low SIF ranges. Possible reasons for the discrepancy between the micro- and macroscopic FCG rates at low values of the SIF are analyzed. It has also been noted that FS is easier to detect on the fracture surface of degraded steel. Hydrogen embrittlement of steel during operation promotes secondary cracking along the FS, making them easier to detect and quantify. It is shown that the invariable value of the microscopic FCG rate at a low SIF range in the operated steel is lower than observable for the steel in the initial state. Secondary cracking of the operated steel may have contributed to the formation of a typical FS pattern along the entire crack front at a lower FCG rate than in unoperated steel.

Highlights

  • The rapid development of computer and information technologies, as well as information processing systems and artificial intelligence, leads to their increasing involvement in various fields of science and technology

  • Based on the analysis of both types of fatigue crack growth (FCG) rates for a wide range of structural materials, it was concluded that basically both rates begin to coincide either during high-temperature tests or in areas with high stress intensity factor (SIF) in the kinetic diagrams of FCG, when high levels of metal deformation in the pre-fracture zone are achieved in almost all grains along the crack front

  • The implementation of the method involves the following sequence of actions: the recognition and selection of fatigue striations by binarization of the image according to the principle of local minima; the rotation of the fragments highlighted in the image with the clearest lines corresponding to the striations until they reach a horizontal orientation using the Hough transform; the estimation of the spacing between the nearest fatigue striations by step-by-step calculation of the vertical distances between the lines corresponding to them or by estimating the average distance between them, taking into account only solid lines

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Summary

Introduction

The rapid development of computer and information technologies, as well as information processing systems and artificial intelligence, leads to their increasing involvement in various fields of science and technology. Image processing and pattern recognition methods are widely used in non-destructive testing and technical diagnostics [1,2,3] They are especially used in radiography, for coating condition monitoring on structural elements of important structures and for rust detection [4,5,6], for condition monitoring and the diagnostics of complex mechanisms [7], followed by quantitative fractography and metallography and so forth [8]. Correlative lightelectron fractography technology is used to increase the accuracy of FS analysis in metal alloys [17] These publications indicate the need to develop and improve methods for the processing of fractographic images of fracture surfaces, which would contribute to a more accurate assessment of the FCG rate at the microscopic level by assessing the quantitative characteristics of typical fracture surface elements

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