缺陷检测的自动超声图像分析方法

G. Corneloup, B. Cornu, I. Magnin, M. Perdrix
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引用次数: 0

摘要

超声检查焊缝提出了众所周知的信号受这种奥氏体钢的干扰,解释材料类型的焊接问题。Cadarache核研究中心开发的JUKEBOX超声成像系统基于对x、Y扫描获得的整体图像的处理,在缺陷定位和表征的一般领域提供了缺陷改进。(X,时间图像是通过对输入信号进行采样而形成的。在y轴上平移的一系列平行图像也是可用的。作者提出了一种基于分析(X,time)图像上记录的最大值和最小值的时间轴位置的检测方法。当遇到缺陷时,该位置在统计上是稳定的,并且在伪噪声条件下具有足够的随机性,可以构成判别参数。调查包括计算跟踪方差:然后将该参数考虑到检测目的。与平行图像的相关性提高了检测的可靠性。在对人工缺陷的测试中,信噪比显著增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Ultrasonic Image Analysis Method for Defect Detection
Ultrasonic examination of seams raises well known signals perturbed by this austenitic steel weld problems of interpreting type of material. The JUKEBOX ultrasonic imaging system developed at the Cadarache Nuclear Research Center provides a malor improvement in the general area of defect localization and characterization, based on processing overall images obtained by iX,Y) scanning. (X,timel images are formed by ~uxtaposing input signals. A series of parallel images shifted on the Y-axis is also available. The authors present a novel deCect detection method based on analysing the timeline positions of the maxima and minima recorded on (X,time) images. This position is statistically stable when a defect is encoutered, and is random enough under spurious noise conditions to constitute a discriminating parameter. The investigation involves calculating the trace variance: this parameter is then taken into account for detection purposes. Correlation with parallel images enhances detection reliability. A significant increase in the signal-to-noise ratio during tests on artificial defects is shown.
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