基于Gauss调制脉冲模型的超声信号提取算法

周海鹏; 韩赞东; 都东; 陈以方

doi:10.16511/j.cnki.qhdxxb.2019.21.003

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清华大学学报（自然科学版） ›› 2019, Vol. 59 ›› Issue (2) : 96-102. DOI: 10.16511/j.cnki.qhdxxb.2019.21.003

机械工程

基于Gauss调制脉冲模型的超声信号提取算法

周海鹏, 韩赞东, 都东, 陈以方

作者信息 +

Ultrasonic signal extraction algorithm based on a Gaussian modulated pulse model

ZHOU Haipeng, HAN Zandong, DU Dong, CHEN Yifang

Author information +

文章历史 +

摘要

奥氏体材料的厚壁焊缝是焊缝超声检测的难点，由于焊缝组织晶粒粗大，超声散射与衰减严重，检测信号中含有大量噪声信号，因此需要通过信号处理提高其信噪比。该文提出了一种基于Gauss调制脉冲（GMP）模型的超声检测信号提取算法，使用参考信号对原始信号进行互相关滤波，并基于GMP模型对滤波结果进行信号分解，由信号特征直接估计各信号分量的控制参数。先后设计了仿真实验及超声检测实验以验证算法性能，结果表明：该算法可以有效提取超声检测信号中的缺陷信息，为厚壁焊缝缺陷信号分析、焊缝检测算法优化等相关应用奠定基础。

Abstract

Austenitic thick-wall welds are difficult to evaluate using ultrasonic testing because the ultrasonic waves are scattered and attenuated by the coarse grain microstructure. The ultrasonic signals then contain much noise with signal processing needed to reduce the noise. This paper presents an ultrasonic signal extraction algorithm based on the Gaussian modulated pulse (GMP) model to improve the signal processing. The original signals are filtered by a cross-correlation method and then the filtered signals are decomposed to acquire the control parameters for each component based on the GMP model and the signal features. Simulations and experiments verify the algorithm's performance. This algorithm can extract useful information about defects from ultrasonic signals as the foundation for further analyses of thick-wall welds for defect information analyses and inspection method optimization.

导出引用

周海鹏, 韩赞东, 都东, 陈以方. 基于Gauss调制脉冲模型的超声信号提取算法[J]. 清华大学学报（自然科学版）. 2019, 59(2): 96-102 https://doi.org/10.16511/j.cnki.qhdxxb.2019.21.003

ZHOU Haipeng, HAN Zandong, DU Dong, CHEN Yifang. Ultrasonic signal extraction algorithm based on a Gaussian modulated pulse model[J]. Journal of Tsinghua University(Science and Technology). 2019, 59(2): 96-102 https://doi.org/10.16511/j.cnki.qhdxxb.2019.21.003

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基金

国家自然科学基金资助项目（51375258）

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收稿日期	出版日期
2018-09-11	2019-02-15
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2019-02-16

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