基于回波去噪的扩散焊接超声C扫描成像优化方法

李钰, 蒋音盈, 常青

doi:10.3969/j.issn.1007-130X.2026.05.010

计算机工程与科学 >

2026 , Vol. 48 >Issue 5: 865 - 875

DOI: https://doi.org/10.3969/j.issn.1007-130X.2026.05.010

图形与图像

基于回波去噪的扩散焊接超声C扫描成像优化方法

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（华东理工大学信息科学与工程学院，上海 200237）

收稿日期: 2024-05-09

修回日期: 2024-11-03

网络出版日期: 2026-05-21

基金资助

国家自然科学基金（51875350）

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An optimized ultrasonic C-scan imaging method for diffusion bonding based on echo denoising

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(School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China)

Received date: 2024-05-09

Revised date: 2024-11-03

Online published: 2026-05-21

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摘要

针对无损检测领域中的钛合金扩散焊接界面缺陷检测这一难点问题，为了提高微小缺陷的检测能力，提出一种基于回波去噪的扩散焊接超声C扫描成像优化方法，通过利用EEMD分解结合小波软阈值去噪重构超声回波信号实现降噪，并根据微小缺陷界面波的特征优化成像方法，以峰谷差值作为新的特征值代替闸门幅值进行C扫描成像以突出微小缺陷；同时结合图像增强及去噪技术进一步优化成像质量，提高缺陷检测能力。在人工缺陷试样上的实际测试结果表明，相较于现有常规超声C扫描成像和其他对比成像方法，所提方法检出缺陷长度与实际金相尺寸误差更小，能有效检出试样中包含的微小缺陷。

关键词： 超声检测; 扩散焊接; 微小缺陷; 成像优化; 特征值

本文引用格式

李钰, 蒋音盈, 常青 . 基于回波去噪的扩散焊接超声C扫描成像优化方法[J]. 计算机工程与科学, 2026 , 48(5) : 865 -875 . DOI: 10.3969/j.issn.1007-130X.2026.05.010

Abstract

Aiming at the challenging issue of titanium alloy diffusion bonding interface defect detection in the field of nondestructive testing, an optimized ultrasonic C-scan imaging method for diffusion bonding based on echo denoising is proposed to enhance the detection capability for minute defects. This method achieves noise reduction by utilizing ensemble empirical mode decomposition (EEMD) combined with wavelet soft-threshold denoising to reconstruct ultrasonic echo signals. The imaging method is optimized according to the characteristics of interface waves from minute defects, employing the peak-to-valley difference as a new feature value instead of the gate amplitude for C-scan imaging to highlight minute defects. Additionally, image enhancement and denoising techniques are integrated to further optimize imaging quality and improve defect detection capability. Practical testing on artificial defect samples demonstrates that, compared to existing conventional ultrasonic C-scan imaging and other comparative imaging methods, the proposed method exhibits smaller errors between the detected defect lengths and the actual metallographic dimensions, effectively detecting minute defects within the specimens.

Key words： ultrasonic detection; diffusion bonding; minute defect; imaging optimization; feature value

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