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X-ray imaging techniques have an enormous potential to understand the microstructure, its evolution, and its link to mechanical, thermal, and transport properties. In this lecture we report the use of a powerful, yet not so wide-spread, set of X-ray techniques based on refraction effects. X-ray refraction allows determining the internal specific surface of materials (surface per unit volume) in a non-destructive fashion, position and orientation sensitive, and with a nanometric detectability. We demonstrate showcases of ceramics and composite materials, where microstructural parameters could be achieved in a way unrivalled even by high-resolution techniques such as electron microscopy or computed tomography. We present in situ analysis of the damage evolution during tensile load and the identification of void formation in parts produced by selective laser melting.
The detection and characterization of surface breaking cracks in steel prior to damage is a technologically as well as economically important task especially for safety-relevant structures. Detection of small cracks already during the steel production process might significantly reduce the risk of failure and reduce production costs due to an obsolete post-processing.
However, the hostile environmental conditions (high temperature specimens) together with very strict requirements in current steel production (production speeds, in-line testing and evaluation) are challenging and render many well-established NDE techniques hardly applicable.
We present an approach to use laser thermographic testing as a fast, remote and contactless NDE method, that addresses these challenges and might ultimately allow for online crack detection.
The basic idea of laser thermographic testing, introduced by Kubiak in 1968, is the monitoring of the heat flow as induced by local heating. Disturbances within the heat flow generated by the presence of surface cracks can then be analyzed by image processing algorithms, as we have shown in previous work.
The aim of the presented work is to advance laser thermographic testing to be applicable to the specific conditions of steel production environments. This purpose was met by the development of a laboratory setup that allows us to simulate production conditions, as rolling speed, specimen temperature, laser heating power and study their influence on crack detection performance. This parametric study enabled us to develop and improve data processing and crack detection algorithms with the final goal of providing optimized in-line crack detection. The studies were accompanied by comprehensive FEM simulations to intensify the understanding of the contrast formation as well as the crucial parameters influencing the performance of the method.
Deutsche Bahn periodically inspects hollow railway axles for fatigue cracks on the outer surface with mechanized ultrasonic inspection systems. According to the current standard for the inspection of railway axles, the capability of the inspection system to detect these cracks has to be demonstrated on the saw-cut type artificial defects. However, the geometry and the ultrasonic response of the real cracks that can occur on the outer surface of the axle are different from the saw-cut. Furthermore, it is demonstrated that the position and the orientation of the cracks are also important factors that influence the crack detectability. It is proposed to evaluate the influence of all factors on the detection of the cracks using the multi-parameter reliability model. The model uses numerical simulation and experiments to comprehensively address the influence of several factors on the probability of detection.