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使用参数流形映射进行超声缺陷表征。

Ultrasonic defect characterization using parametric-manifold mapping.

作者信息

Velichko A, Bai L, Drinkwater B W

机构信息

Department of Mechanical Engineering, University of Bristol, Queens Building, University Walk, Bristol BS8 1TR, UK.

出版信息

Proc Math Phys Eng Sci. 2017 Jun;473(2202):20170056. doi: 10.1098/rspa.2017.0056. Epub 2017 Jun 7.

Abstract

The aim of ultrasonic non-destructive evaluation includes the detection and characterization of defects, and an understanding of the nature of defects is essential for the assessment of structural integrity in safety critical systems. In general, the defect characterization challenge involves an estimation of defect parameters from measured data. In this paper, we explore the extent to which defects can be characterized by their ultrasonic scattering behaviour. Given a number of ultrasonic measurements, we show that characterization information can be extracted by projecting the measurement onto a parametric manifold in principal component space. We show that this manifold represents the entirety of the characterization information available from far-field harmonic ultrasound. We seek to understand the nature of this information and hence provide definitive statements on the defect characterization performance that is, in principle, extractable from typical measurement scenarios. In experiments, the characterization problem of surface-breaking cracks and the more general problem of elliptical voids are studied, and a good agreement is achieved between the actual parameter values and the characterization results. The nature of the parametric manifold enables us to explain and quantify why some defects are relatively easy to characterize, whereas others are inherently challenging.

摘要

超声无损评估的目的包括缺陷的检测与表征,而了解缺陷的性质对于评估安全关键系统的结构完整性至关重要。一般来说,缺陷表征的挑战在于根据测量数据估计缺陷参数。在本文中,我们探讨了缺陷在多大程度上可以通过其超声散射行为来表征。给定若干超声测量值,我们表明可以通过将测量值投影到主成分空间中的参数流形上来提取表征信息。我们表明,该流形代表了远场谐波超声可获得的全部表征信息。我们试图理解此信息的本质,从而对原则上可从典型测量场景中提取的缺陷表征性能给出明确的说明。在实验中,研究了表面开口裂纹的表征问题以及更一般的椭圆形空洞问题,实际参数值与表征结果之间取得了良好的一致性。参数流形的性质使我们能够解释和量化为什么有些缺陷相对容易表征,而有些则本质上具有挑战性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a07f/5493948/52fb52a5ac4f/rspa20170056-g1.jpg

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