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Further Development of Image Processing Algorithms to Improve Detectability of Defects in Sonic IR NDE

机译:图像处理算法的进一步发展,提高声波IR NDE中缺陷的可检测性

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Sonic Infrared imaging (SIR) technology is a relatively new NDE technique that has received significant acceptance in the NDE community. SIR NDE is a super-fast, wide range NDE method. The technology uses short pulses of ultrasonic excitation together with infrared imaging to detect defects in the structures under inspection. Defects become visible to the IR camera when the temperature in the crack vicinity increases due to various heating mechanisms in the specimen. Defect detection is highly affected by noise levels as well as mode patterns in the image. Mode patterns result from the superposition of sonic waves interfering within the specimen during the application of sound pulse. Mode patterns can be a serious concern, especially in composite structures. Mode patterns can either mimic real defects in the specimen, or alternatively, hide defects if they overlap. In last year's QNDE, we have presented algorithms to improve defects detectability in severe noise. In this paper, we will present our development of algorithms on defect extraction targeting specifically to mode patterns in SIR images.
机译:声波红外成像(SIR)技术是一种相对较新的NDE技术,在NDE社区中得到了显着的认可。 NDE先生是一种超快速,广泛的NDE方法。该技术采用超声波激发的短脉冲与红外成像一起检测检查中的结构中的缺陷。当裂缝附近的温度由于样本中的各种加热机制而增加时,缺陷可见IR摄像机。缺陷检测受到噪声水平的高度影响以及图像中的模式模式。模式模式由声波在施加声音脉冲期间对样本内的声波进行干扰的叠加产生。模式模式可能是一个严重的问题,尤其是复合结构。模式模式可以模仿样本中的真实缺陷,或者可选地,如果它们重叠,则隐藏缺陷。在去年的QNDE中,我们提出了算法,以改善严重噪声的缺陷可检测性。在本文中,我们将在特定于SIR图像中专门针对模式模式的缺陷提取算法的发展。

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