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用于无损检测的单侧空气耦合超声脉冲回波技术的二维模拟

Two-dimensional simulation of the single-sided air-coupled ultrasonic pitch-catch technique for non-destructive testing.

作者信息

Delrue Steven, Van Den Abeele Koen, Blomme Erik, Deveugele Jurgen, Lust Pieter, Matar Olivier Bou

机构信息

K.U.Leuven Campus Kortrijk, 8500 Kortrijk, Belgium.

出版信息

Ultrasonics. 2010 Feb;50(2):188-96. doi: 10.1016/j.ultras.2009.08.005. Epub 2009 Aug 12.

Abstract

Non-contact air-coupled ultrasonic inspection of materials using single-sided access offers interesting possibilities for the development of in-line non-destructive testing (NDT) systems. This contribution reports observations and simulations obtained from a single-sided air-coupled pitch-catch configuration. The pitch-catch technique involves a set-up in which transmitter and receiver are located at the same side of the test object. Sound waves, reflected once or multiple times from the back-wall of the object or refracted by a discontinuity, are recorded and analyzed for visualization. The feasibility of the technique is demonstrated, experimentally, in the case of artificial defects in aluminium samples. Depending on the configuration one or more ultrasonic images of the defect can be observed, their number and relative position containing information about the location of the defect. The experiments are simulated using two distinctive methods. The first simulation is based on a ray tracing (shadow) approach, the second method uses a spectral solution implemented within COMSOL. Both simulation methods allow simple prediction of the response images in experimental conditions with supplementary levels of complexity, which will assist the development and optimization of online inspection techniques.

摘要

使用单面检测的非接触式空气耦合超声材料检测为在线无损检测(NDT)系统的发展提供了有趣的可能性。本论文报告了从单面空气耦合的斜射检测配置中获得的观测结果和模拟结果。斜射检测技术涉及一种设置,其中发射器和接收器位于测试对象的同一侧。从对象后壁反射一次或多次的声波,或由不连续处折射的声波,被记录并分析以进行可视化。该技术的可行性在铝样品中的人工缺陷情况下通过实验得到了证明。根据配置,可以观察到缺陷的一个或多个超声图像,它们的数量和相对位置包含有关缺陷位置的信息。实验使用两种不同的方法进行模拟。第一种模拟基于射线追踪(阴影)方法,第二种方法使用在COMSOL中实现的频谱解。两种模拟方法都可以在具有附加复杂程度的实验条件下简单地预测响应图像,这将有助于在线检测技术的开发和优化。

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