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Ultrasonic modelling of coarse grained austenitic steel

机译:粗粒奥氏体钢超声波建模

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Railway crossings are subject to repetitive explosive impact collisions from rolling stock. Such repetitive action acts as a catalyst for fatigue cracking, which compromises the structural integrity of these safety critical components. For this reason, crossings are manufactured from high manganese steel, which is highly resistant to fatigue cracking due to its work hardening properties. Due to the inherent coarse grained structure and anisotropic material properties, in-service inspection of crossings using conventional ultrasonic techniques is ineffective. Consequently inspection is limited to surface techniques such as visual and dye-penetrant. A solution has been developed which enables reliable volumetric inspection of crossings. The technique known as Synthetic Aperture Focusing Technique (SAFT), offers enhanced flaw resolution and signal to noise ratio (SNR), due to its ability to reduce grain noise through spatial averaging. This paper presents the development of a procedure to accurately model the effect of coarse grained, austenitic steel on ultrasonic inspection. The coarse grains and anisotropy result in high levels of beam scattering, energy absorption and poor SNR. These effects were simulated using the CIVA software and compared with experimental results. This study led to the design of an annular phased array transducer capable of full volume inspection of the manganese steel crossings.
机译:铁路交叉口受到滚动股票的重复爆炸性冲击。这种重复动作用作疲劳裂缝的催化剂,这损害了这些安全关键部件的结构完整性。因此,由于其加工硬化性能,交叉由高锰钢制成,这对疲劳裂缝具有高度耐疲劳。由于固有的粗粒结构和各向异性材料特性,使用常规超声波技术的交叉在式检查是无效的。因此,检查限于表面技术,例如视觉和染料渗透剂。已经开发了一种解决方案,其能够可靠地检查过境点。称为合成孔径聚焦技术(SAFT)的技术,由于其通过空间平均来降低粒度噪声,可以提高漏洞分辨率和信噪比(SNR)。本文介绍了一种准确模拟粗粒,奥氏体钢对超声波检查的效果的程序的发展。粗粒和各向异性导致高水平的光束散射,能量吸收和差的SNR。使用Civa软件模拟这些效果,并与实验结果进行了比较。该研究导致了一种能够全体积检查锰钢口的环形相控阵换能器的设计。

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