Stockwell变换在超声信号缺陷模式识别中的可行性

K. Sudheera, N. Nandhitha, N. Ganesh, P. Nanekar, B. Venkatraman, B. Sheela Rani
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引用次数: 0

摘要

超声检测是厚壁焊件缺陷检测中广泛应用的无损检测技术。它是一种间接技术,需要对信号进行分析以表征缺陷。这些信号的人工解释本质上是主观的,依赖于个人的专业知识。因此,范式已经转向自动信号分析。本文在不使用人工神经网络的情况下,成功地在同类缺陷中建立了一种模式。利用斯托克韦尔变换对信号进行分析,确定信号的模式。定量表征也做了平均值,标准差,均方根值,峰均方根比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feasibility of Stockwell transform for flaw pattern recognition in ultra sonic signals
Ultrasonic Testing is the widely used NDT technique for flaw detection in thick walled weldments. It is an indirect technique and the signals are to be analyzed in order to characterize the flaw. Manual interpretation of these signals is subjective in nature and is dependent on the expertise of the individual. Hence the paradigm has shifted to automated signal analysis. In this paper a successful attempt has been made to develop a pattern among the flaws of same type without using Artificial Neural Networks. Here, the signals are analyzed with Stockwell transform and the pattern is determined. Also quantitative characterization is done with mean, standard deviation, root mean square value, peak to rms ratio.
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